Search results for: EXPLAINABLE CLASSIFIERS, COUNTERFACTUAL APPROACH, BIAS DETECTION
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublicationThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Application of a stochastic compartmental model to approach the spread of environmental events with climatic bias
PublicationWildfires have significant impacts on both environment and economy, so understanding their behaviour is crucial for the planning and allocation of firefighting resources. Since forest fire management is of great concern, there has been an increasing demand for computationally efficient and accurate prediction models. In order to address this challenge, this work proposes applying a parameterised stochastic model to study the propagation...
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Direct spectrum detection based on Bayesian approach
PublicationThe paper investigates the Bayesian framework's performance for a direct detection of spectrum parameters from the compressive measurements. The reconstruction signal stage is eliminated in by the Bayesian Compressive Sensing algorithm, which causes that the computational complexity and processing time are extremely reduced. The computational efficiency of the presented procedure is significantly...
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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An A-Team approach to learning classifiers from distributed data sources
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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An Approach to the Detection of Bank Robbery Acts Employing Thermal Image Analysis
PublicationA novel approach to the detection of selected security-related events in bank monitoring systems is presented. Thermal camera images are used for the detection of people in difficult lighting conditions. Next, the algorithm analyses movement of objects detected in thermal or standard monitoring cameras using a method evolved from the motion history images algorithm. At the same time, thermal images are analyzed in order to detect...
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MultiRegional PCA for leakage detection and localisation in DWDS - approach
PublicationMonitoring is one of the most important parts in advanced control of complex dynamic systems. Information about systems behavior, including failures indicating, enables for efficient control. The chapter describes an approach to detection and localisation of pipe leakage in Drinking Water Distribution Systems (DWDS) representing complex and distributed dynamic system of large scale. Proposed MultiRegional Principal Component Analysis...
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Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network
PublicationThe contribution of this paper is to show the opportunities for using the compressive sensing (CS) technique for detecting harmonics in a frequency sparse signal. The signal in a ship’s electrical network, polluted by harmonic distortions, can be modeled as a superposition of a small number of sinusoids and the discrete Fourier transform (DFT) basis forms its sparse domain. According to the theory of CS, a signal may be reconstructed...
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Real-time PCR approach in dermatophyte detection and Trichophyton rubrum identification
PublicationDermatophytes are keratinophilic molds that infect human hair, nails and skin. Diagnosis of dermatophytosis is based on morphological, serological and biochemical features. However, identification is difficult and laborious due to similarities between microorganisms. Thus, there is considerable interest to develop mycological diagnostic procedures based on molecular biology methods. In this study, fast, two-step DNA extraction...
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Cointegration approach for temperature effect compensation in Lamb-wave-based damage detection
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Object-oriented approach to oil spill detection using ENVISAT ASAR images
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Multifrequency Nanoscale Impedance Microscopy (m-NIM): A novel approach towards detection of selective and subtle modifications on the surface of polycrystalline boron-doped diamond electrodes
PublicationIn this paper, we describe the modification of Nanoscale Impedance Microscopy (NIM), namely, a combination of contact-mode atomic force microscopy with local impedance measurements. The postulated approach is based on the application of multifrequency voltage perturbation instead of standard frequency-by-frequency analysis, which among others offers more time-efficient and accurate determination of the resultant impedance spectra...
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Cointegration and wavelet-analysis-based approach for Lamb-wave-based structural damage detection
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Stationarity-Based Approach for the Selection of Lag Length in Cointegration Analysis Used for Structural Damage Detection
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Fast-response optoelectronic detection of explosives’ residues from the nitroaromatic compounds detonation: field studies approach
PublicationWe are presenting an application of optoelectronic nitrogen dioxide (NO2) analyzer based on cavity enhanced absorption spectroscopy in the detection of traces of explosives after detonation. It has been shown that the analyzer using blue-violet laser is able to detect explosive residues after the detonation of various amounts of nitroaromatic compounds (75g-1kg) with higher efficiency than the HPLC soil sample testing equipment,...
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Wioleta Kucharska dr hab. inż.
PeopleWioleta Kucharska holds a position as an Associate Professor at the Faculty of Management and Economics of the Gdansk TECH, Gdansk University of Technology, Fahrenheit Universities Union, Poland. She authored 74 peer-reviewed studies published with Wiley, Springer, Taylor & Francis, Emerald, Elsevier, IGI Global, Routledge, and by members of international conferences committees. She reviews international journals (83 revisions...
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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublicationAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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What should we know when choosing feather, blood, egg or preen oil as biological samples for contaminants detection? A non-lethal approach to bird sampling for PCBs, OCPs, PBDEs and PFASs
PublicationBirds are considered as good bio-monitors and they can provide highly valuable data about the level of contamination in their habitat. During the design of biomonitoring studies one of the first issues after choosing species is the choice of biological material. Non-lethally collected samples have recently been gaining greater attention as they offer several ethical and practical advantages. However, not all sample matrices are...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Zdzisław Kowalczuk prof. dr hab. inż.
PeopleZdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...
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Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection
PublicationAs a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...
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Adding Interpretability to Neural Knowledge DNA
PublicationThis paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine...
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PCA based Fault Tolerant MPC
PublicationThis chapter presents a Fault Tolerant - Model Predictive Control (FT-MPC) schemes for sensor faults accommodation. A Fault Detection and Isolation (FDI) Unit, which is an integral part of FT-MPC system, is based on the Principal Component Analysis (PCA) method. Introduced approach enables efficient bias and drift faults accommodation in single, as well as simultaneous faults case. Simple simulation exercise is presented.Rozdział...
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Improving automatic surveillance by sound analysis
PublicationAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublicationHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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Buzz-based honeybee colony fingerprint
PublicationNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Diagnostic Models and Estimators for LDI in Transmission Pipelines
PublicationThis article considers and compares four analytical models of the pipeline flow process for leak detection and location tasks. The synthesis of these models is briefly outlined. Next, the methodology for generating data and diagnosing pipes is described, as well as experimental settings, assumptions and implemented scenarios. Finally, the quality of model-based diagnostic estimators has been evaluated for their bias, standard deviations...
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Multiscaled Hybrid Features Generation for AdaBoost Object Detection
PublicationThis work presents the multiscaled version of modified census features in graphical objects detection with AdaBoost cascade training algorithm. Several experiments with face detector training process demonstrate better performance of such features over ordinal census and Haar-like approaches. The possibilities to join multiscaled census and Haar features in single hybrid cascade of strong classifiers are also elaborated and tested....
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Electrical responses of Graphene-Silicon Schottky diodes toward nitrogen dioxide and tetrahydrofuran under irradiation
Open Research DataGraphene-Silicon Schottky junctions were utilized as gas sensors toward inorganic (nitrogen dioxide) and organic (tetrahydrofuran) gas qualitative and quantitative detection. The electrical responses of the sensors were collected in the form of current-voltage characteristics and measurements of current in time domain for a selected voltage bias. The...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Asynchronous Charge Carrier Injection in Perovskite Light-Emitting Transistors
PublicationUnbalanced mobility and injection of charge carriers in metal-halide perovskite light-emitting devices pose severe limitations to the efficiency and response time of the electroluminescence. Modulation of gate bias in methylammonium lead iodide light-emitting transistors has proven effective in increasing the brightness of light emission up to MHz frequencies. In this work, a new approach is developed to improve charge carrier...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublicationThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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How to model ROC curves - a credit scoring perspective
PublicationROC curves, which derive from signal detection theory, are widely used to assess binary classifiers in various domains. The AUROC (area under the ROC curve) ratio or its transformations (the Gini coefficient) belong to the most widely used synthetic measures of the separation power of classification models, such as medical diagnostic tests or credit scoring. Frequently a need arises to model an ROC curve. In the biostatistical...
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The AFM micrographs of gold nanoparticles on silicon substrate
Open Research DataThe dataset contains the first approach towards AFM topographic imaging of gold nanoparticles synthesized and immobilized on the silicon surface. Measurements were made in the semi-contact mode on the NTEGRA Prima device, manufactured by NT-MDT. Scans were performed with amplitude detection at an operating value of 60% of the free oscillation amplitude....
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Affective reactions to playing digital games
PublicationThe paper presents a study of emotional states during a gameplay. An experiment of two-player Tetris game is reported, followed by the analysis of the results - self-reported emotional states as well as physiological signals measurements interpretation. The study reveals the diversity of emotional reactions and concludes, that a representative player's emotional model is hard to define. Instead, an adaptive approach to emotion...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublicationThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Two Stage SVM and kNN Text Documents Classifier
PublicationThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Layered background modeling for automatic detection of unattended objects in camera images
PublicationAn algorithm for automatic detection of unattended objects in video camera images is presented. First, background subtraction is performed, using an approach based on the codebook method. Results of the detection are then processed by assigning the background pixels to time slots, based on the codeword age. Using this data, moving objects detected during a chosen period may be extracted from the background model. The proposed approach...
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Sonar Pulse Detection Using Chirp Rate Estimation and CFAR Algorithms
PublicationThis paper presents a new approach to sonar pulse detection. The method uses chirp rate estimators and algorithms for the adaptive threshold, commonly used in radiolocation. The proposed approach allows detection of pulses of unknown parameters, which may be used in passive hydrolocation or jamming detection in underwater communication. Such an analysis is possible thanks to a new kind of imaging, which presents signal energy in...
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A review of emotion recognition methods based on keystroke dynamics and mouse movements
PublicationThe paper describes the approach based on using standard input devices, such as keyboard and mouse, as sources of data for the recognition of users’ emotional states. A number of systems applying this idea have been presented focusing on three categories of research problems, i.e. collecting and labeling training data, extracting features and training classifiers of emotions. Moreover the advantages and examples of combining standard...
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Assessment of copper surface coverage with corrosion inhibitor using AFM-based local electrical measurements
PublicationThe paper presents a new method of assessment of metal surface coverage with corrosion inhibitor and thus of inhibitor protective performance. It is based on the atomic force microscopy measurement performed in a contact mode. Apart from topography images the proposed approach allows acquisition of local DC maps and local electrical impedance spectra via application of DC bias voltage or AC perturbation signal between the conductive...
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Enhanced gas sensing by graphene-silicon Schottky diodes under UV irradiation
PublicationThe effect of ultraviolet (UV) or blue irradiation on graphene/n-doped silicon Schottky junctions toward gas sensing was investigated. Schottky diodes were subjected to oxidizing nitrogen dioxide (NO2, 1–3 ppm) and reducing tetrahydrofuran (THF, 50–200 ppm), showing significantly different responses observed on the currentvoltage (I-V) characteristics, especially under UV light (275 nm). NO2 affected the resistive part of the forward region...
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A double-talk detector using audio watermarking
Publicationa novel approach to double-talk detection in the acoustic echo canceler is proposed. a hidden signature is embedded into the arriving signal, using the echo-hiding method. next detection of the presence of this signature in the microphone signal is performed. the results of the signature detection may be used by the acoustic echo canceler to stop or restart the adaptation process.
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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An Overview of Image Analysis Techniques in Endoscopic Bleeding Detection
PublicationAuthors review the existing bleeding detection methods focusing their attention on the image processing techniques utilised in the algorithms. In the article, 18 methods were analysed and their functional components were identified. The authors proposed six different groups, to which algorithms’ components were assigned: colour techniques, reflecting features of pixels as individual values, texture techniques, considering spatial...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one should choose the so-called estimation bandwidth, related to the effective width of the local analysis window. The choice should comply with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive estimation variance. The paper presents a novel method...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublicationBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Human-Computer Interface Based on Visual Lip Movement and Gesture Recognition
PublicationThe multimodal human-computer interface (HCI) called LipMouse is presented, allowing a user to work on a computer using movements and gestures made with his/her mouth only. Algorithms for lip movement tracking and lip gesture recognition are presented in details. User face images are captured with a standard webcam. Face detection is based on a cascade of boosted classifiers using Haar-like features. A mouth region is located in...
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Network society: a concept of smart information management
PublicationAutomatic enhancement of Internet broadcasted news has been recently gaining increasing importance and interest. Existing applications and models of textual Event Detection in online media are based on the analysis of news distributed via RSS (Rich Site Summary called also Really Simple Syndication) channels or available at news websites. It assumes that each piece of news is equally available to the reader and, therefore, describes...
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Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublicationIn the paper, the approach to seafloor characterisation is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry and underwater object detection and imaging, are also the promising tool in seafloor characterization and classification, having several advantages over conventional single beam echosounders. The proposed approach relies on the combined, concurrent use...
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A simple modification of PCR thermal profile applied to evade persisting contamination
PublicationThe polymerase chain reaction (PCR), one of the most commonly applied methods of diagnostics and molecular biology has a frustrating downside known as the false positive signal or contamination. Several solutions to avoid and to eliminate PCR contaminations have been worked out to date but the implementation of these solutions to laboratory practice may be laborious and time consuming. A simple approach to circumvent the problem...
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Integration of protein tethering in a rapid and label-free SERS screening platform for drugs of abuse
PublicationSurface enhanced Raman spectroscopy (SERS) has emerged as a promising technique for the rapid and ultrasensitive detection of molecular species such as drugs of abuse in biofluids. Yet, it remains a significant challenge to create a viable screening tool for multiple drug classes, owing to the lack of affinity of certain species for the SERS substrate and to the matrix interference in complex media. Here we report a protein tethering...
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Extraction of stable foreground image regions for unattended luggage detection
PublicationA novel approach to detection of stationary objects in the video stream is presented. Stationary objects are these separated from the static background, but remaining motionless for a prolonged time. Extraction of stationary objects from images is useful in automatic detection of unattended luggage. The proposed algorithm is based on detection of image regions containing foreground image pixels having stable values in time and...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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A low complexity double-talk detector based on the signal envelope
PublicationA new algorithm for double-talk detection, intended for use in the acoustic echo canceller for voice communication applications, is proposed. The communication system developed by the authors required the use of a double-talk detection algorithm with low complexity and good accuracy. The authors propose an approach to doubletalk detection based on the signal envelopes. For each of three signals: the far-end speech, the microphone...
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Self-Testing of Analog Parts Terminated by ADCs Based on Multiple Sampling of Time Responses
PublicationA new approach for self-testing of analog parts terminated by analog-to-digital converters in mixed-signal electronic microsystems controlled by microcontrollers is presented. It is based upon a new fault diagnosis method using a transformation of the set of voltage samples of the time response of a tested analog part to a square impulse into localization curves placed in a multidimensional measurement space. The method can be used...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Video Classification Technology in a Knowledge-Vision-Integration Platform for Personal Protective Equipment Detection: An Evaluation
PublicationThis work is part of an effort for the development of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. This paper focuses on hazards resulted from the non-use of personal protective equipment (PPE), and examines a few supervised learning techniques to compose the proposed system for the purpose of recognition of three protective...
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Non-volatile molecular composition and discrimination of single grape white of chardonnay, riesling, sauvignon blanc and silvaner using untargeted GC–MS analysis
PublicationThis study developed and applied a GC–MS method aiming at molecular fingerprinting of 120 commercial single grape white wines (Chardonnay, Riesling, Sauvignon Blanc and Silvaner) for possible authentication according to grape variety. The method allowed detection of 372 peaks and tentative identification of 146 metabolites including alcohols, organic acids, esters, amino acids and sugars. The grape variety effect explained 8.3%...
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublicationThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...
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A framework for detection of selfishness in multihop mobile ad hoc networks
PublicationThe paper discusses the need for a fully-distributed selfishness detection mechanism dedicated for multihop wireless ad hoc networks which nodes may exhibit selfish forwarding behaviour. The main contribution of this paper is an introduction to a novel approach for detecting and coping with the selfish nodes. Paper describes a new framework based on Dempster-Shafer Theory called Dempster-Shafer Theory-based Selfishness Detection...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries
PublicationLocalizing instrument parts in video-assisted surgeries is an attractive and open computer vision problem. A working algorithm would immediately find applications in computer-aided interventions in the operating theater. Knowing the location of tool parts could help virtually augment visual faculty of surgeons, assess skills of novice surgeons, and increase autonomy of surgical robots. A surgical tool varies in appearance due to...
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Portable exhaled breath analyzer employing fluctuation-enhanced gas sensing method in resistive gas sensors
PublicationThis paper presents a portable exhaled breath analyser, developed to detect selected diseases. The set-up employs resistive gas sensors: commercial MEMS sensors and prototype gas sensors made of WO3 gas sensing layers doped with various metal ingredients. The set-up can modulate the gas sensors by applying UV light to induce physical changes of the gas sensing layers. The sensors are placed in a tiny gas chamber of a volume...
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Fluctuation-Enhanced Sensing with Organically Functionalized Gold Nanoparticle Gas Sensors Targeting Biomedical Applications
PublicationDetection of volatile organic compounds is a useful approach to non-invasive diagnosis of diseases through breath analysis. Our experimental study presents a newly developed prototype gas sensor, based on organically-functionalized gold nanoparticles, and results on formaldehyde detection using fluctuation-enhanced gas sensing. Formaldehyde was easily detected via intense fluctuations of the gas sensor’s resistance, while the cross-influence...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Recurrent potential pulse technique for improvement of glucose sensing ability of 3D polypyrrole
PublicationIn this work, a new approach for using a 3D polypyrrole (PPy) conducting polymer as a sensing material for glucose detection is proposed. Polypyrrole is electrochemically polymerized on a platinum screen-printed electrode in an aqueous solution of lithium perchlorate and pyrrole. PPy exhibits a high electroactive surface area and high electrochemical stability, which results in it having excellent electrocatalytic properties. The...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublicationShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublicationThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Evaluation of organic coatings condition with AFM-based method
PublicationThe paper presents an atomic force microscopy (AFM)-based approach to evaluation of local protective properties of organic coatings. Apart from topography, it provides local ac and dc characteristics of examined coating. The method consists in application of ac voltage perturbation signal between conductive AFM tip and coated metal substrate. The resulting current is used to determine local impedance characteristics. Both impedance...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Elimination of impulsive disturbances from archive audio files – comparison of three noise pulse detection schemes
PublicationThe problem of elimination of impulsive disturbances (such as clicks, pops, ticks, crackles, and record scratches) from archive audio recordings is considered and solved using autoregressive modeling. Three classical noise pulse detection schemes are examined and compared: the approach based on open-loop multi-step-ahead signal prediction, the approach based on decision-feedback signal prediction, and the double threshold approach,...
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Multimodal Approach For Polysensory Stimulation And Diagnosis Of Subjects With Severe Communication Disorders
Publicationis evaluated on 9 patients, data analysis methods are described, and experiments of correlating Glasgow Coma Scale with extracted features describing subjects performance in therapeutic exercises exploiting EEG and eyetracker are presented. Performance metrics are proposed, and k-means clusters used to define concepts for mental states related to EEG and eyetracking activity. Finally, it is shown that the strongest correlations...
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Multimodal Surveillance Based Personal Protection System
PublicationA novel, multimodal approach for automatic detection of abduction of a protected individual, employing dedicated personal protection device and a city monitoring system is proposed and overviewed. The solution is based on combining four modalities (signals coming from: Bluetooth, fixed and PTZ cameras, thermal camera, acoustic sensors). The Bluetooth signal is used continuously to monitor the protected person presence, and in case...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublicationIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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Damage detection in plates based on Lamb wavefront shape reconstruction
PublicationMany of the current studies in the area of damage detection using elastic wave propagation are based on deploying sensor networks with a large number of piezoelectric transducers to detect small-size cracks. A major limitation of these studies is that cracks are usually larger and have different shapes in real cases. Moreover, using a large number of sensing nodes for damage detection is both costly and computationally intensive....
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Eye Blink Based Detection of Liveness in Biometric Authentication Systems Using Conditional Random Fields
PublicationThe goal of this paper was to verify whether the conditional random fields are suitable and enough efficient for eye blink detection in user authentication systems based on face recognition with a standard web camera. To evaluate this approach several experiments were carried on using a specially developed test application and video database.
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Shore Construction Detection by Automotive Radar for the Needs of Autonomous Surface Vehicle Navigation
PublicationAutonomous surface vehicles (ASVs) are becoming more and more popular for performing hydrographic and navigational tasks. One of the key aspects of autonomous navigation is the need to avoid collisions with other objects, including shore structures. During a mission, an ASV should be able to automatically detect obstacles and perform suitable maneuvers. This situation also arises in near-coastal areas, where shore structures like...
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Biomolecular influenza virus detection based on the electrochemical impedance spectroscopy using the nanocrystalline boron-doped diamond electrodes with covalently bound antibodies
PublicationNew rapid pathogen detection methods with improved cost-effectiveness and efficiency are currently in the focus of the scientists from all over the world. Based on the experiences from the rapid spread of the influenza virus pandemic in 2009 it is clear that the development of the system for early diagnosis of this infection is essential. The crucial stage of the treatment is the detection of the viral infection during its initial...
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Verification of the Parameterization Methods in the Context of Automatic Recognition of Sounds Related to Danger
PublicationW artykule opisano aplikację, która automatycznie wykrywa zdarzenia dźwiękowe takie jak: rozbita szyba, wystrzał, wybuch i krzyk. Opisany system składa się z bloku parametryzacji i klasyfikatora. W artykule dokonano porównania parametrów dedykowanych dla tego zastosowania oraz standardowych deskryptorów MPEG-7. Porównano też dwa klasyfikatory: Jeden oparty o Percetron (sieci neuronowe) i drugi oparty o Maszynę wektorów wspierających....
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublicationThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublicationThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk
PublicationSatellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land...
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Diver Observations by Means of Acoustic Methods
PublicationSearching for objects, especially small ones, moving under water near its the free surface, is always not an easy task. Designing tools for the detection of such targets is a real challenge when the possibility of a terrorist attack is a real threat. This paper presents some aspects of diver detection by means of acoustics methods, both active (side scan sonar) and passive ones (linear receiving antenna). This approach is quite...
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Damage localisation in a stiffened plate structure using a propagating wave
PublicationThe paper presents an application of changes in propagating waves for damage detection in a stiffened aluminium plate. The experimental investigation was conducted on an aluminium plate with riveted two L-shape stiffeners. The wave has been excited with a piezoelectric transducer and measured with the Laser Scanning Doppler Vibrometer. Recorded signals were analysed using the special signal processing techniques developed for damage...
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Hierarchical 2-step neural-based LEGO bricks detection and labeling
PublicationLEGO bricks are extremely popular and allow the creation of almost any type of construction due to multiple shapes available. LEGO building requires however proper brick arrangement, usually done by shape. With over 3700 different LEGO parts this can be troublesome. In this paper, we propose a solution for object detection and annotation on images. The solution is designed as a part of an automated LEGO bricks arrangement. The...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Automatic detection and correction of detuned singing system for use with query-by-humming applications
PublicationThe aim of the paper is to present an idea of using the automatic detection and correction of detuned singing as a subsystem in query-by-humming (QBH) applications. The common approach to searching for a requested song basing on the melody retrieved from hummed pattern usually employs the so-called Parsons code or melody contour. In such a case information about sound pitch is discarded. It was thought out that an additional module...
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Detection and Direction-of-Arrival Estimation of Weak Spread Spectrum Signals Received with Antenna Array
PublicationThis paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the...
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Facial emotion recognition using depth data
PublicationIn this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...
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Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling
PublicationA common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...