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Wyniki wyszukiwania dla: CLASSIFICATION
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Is the Keros classification alone enough to identify patients with the ‘dangerous ethmoid’? An anatomical study
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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A New Classification of the Morphology of Complete Ponticulus Posticus on Cone Beam Computed Tomography
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Affine continuous cellular automata solving the fixed-length density classification problem
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Multi-Label Classification for AIS Data Anomaly Detection Using Wavelet Transform
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Decision classification criteria for ADT in burn diagnostics based on in-vivo animal experiments
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Musical Instrument Classification and Duet Analysis Employing Music Information Retrieval Techniques.
PublikacjaArtykuł przedstawia w sposób przeglądowy prace Katedry Systemów Multimedialnych Politechniki Gdańskiej związane z wyszukiwaniem informacji muzycznej, a w szczególności z klasyfikacją dźwięków instrumentów muzycznych. W opisywanych eksperymentach wykorzystano sztuczne sieci neuronowe.
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe 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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A new approach for an automatic assessment of a neurological condition employing hand gesture classification
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Classification and fingerprinting of kiwi and pomelo fruits by multivariate analysis of chromatographic and spectroscopic data
PublikacjaThe fingerprinting capacity of two analytical techniques, HPLC and UV-Vis spectroscopy in the case of fruits samples (kiwi and pomelo) has been investigated. The multivariate exploratory techniques were used for sample discrimination according to the fruit species and subspecies. The combination of principal component analysis with linear discriminant analysis is opening new directions in the fingerprinting analysis. The classifications...
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Chiral-based optical and electrochemical biosensors: Synthesis, classification, mechanisms, nanostructures, and applications
PublikacjaThis review seeks to collect, summarize, classify and discuss the latest advances in chiral-based optical biosensors. Starting from the identification of chiral molecules, photoluminescence, and electrochemical sensors, applications of chiral structures in biosensing molecules are reviewed. Then, biosensors working on the basis of chirality are classified, followed by summarizing the outcomes of research works on design, synthesis,...
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Data Domain Adaptation in Federated Learning in the Breast Mammography Image Classification Problem
PublikacjaWe are increasingly striving to introduce modern artificial intelligence techniques in medicine and elevate medical care, catering to both patients and specialists. An essential aspect that warrants concurrent development is the protection of personal data, especially with technology's advancement, along with addressing data disparities to ensure model efficacy. This study assesses various domain adaptation techniques and federated...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Minichannel and minigap classification criteria based on the aspect ratio of the minigeometry: A numerical study
PublikacjaA detailed numerical investigation has been carried out to analyze the diabatic flow distribution and velocity profile in 18 minigeometries with various aspect ratios for V-type and I-type flow configurations (for 36 cases) assuming ethanol as a working fluid. The aim of the study is to distinguish the value of the aspect ratio for which the flow in minigeometry starts to be two-dimensional (minigap). Cases with a constant Reynolds...
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Systematic approach to binary classification of images in video streams using shifting time windows
Publikacjain the paper, after pointing out of realistic recordings and classifications of their frames, we propose a new shifting time window approach for improving binary classifications. We consider image classification in tewo steps. in the first one the well known binary classification algorithms are used for each image separately. In the second step the results of the previous step mare analysed in relatively short sequences of consecutive...
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Analyzing the Impact of Simulated Multispectral Images on Water Classification Accuracy by Means of Spectral Characteristics
PublikacjaRemote sensing is widely applied in examining the parameters of the state and quality of water. Spectral characteristics of water are strictly connected with the dispersion of electromagnetic radiation by suspended matter and the absorp-tion of radiation by water and chlorophyll a and b.Multispectral sensor ALI has bands within the ranges of electromagnetic radia-tion: blue and infrared, absent in sensors such as Landsat, SPOT,...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis 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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Brief Literature Review and Classification System of Reliability Methods for Evaluating the Stability of Earth Slopes
PublikacjaThe issue of slope stability is one of the most important and yet most difficult geotechnical problems. Assessing slope stability is particularly difficult because of the many uncertainties involved in the process. To take these uncertainties into account, probabilistic methods are used, and the reliability approach is adopted. There are many methods for reliability assessment of earth slope stability. However, there is no system...
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A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms
PublikacjaThis paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublikacjaArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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The present state of requirements of international association of classification societies (IACS) for wrought aluminium alloys
PublikacjaW referacie przedstawiono aktualną sytuację w zakresie stopów aluminium z serii 5xxx i 6xxx do przeróbki plastycznej, ze szczególnym uwzględnieniem zmian w tym zakresie zapoczątkowanych przez unifikację wymagań w dokumentach nr 25 i 26 opublikowanychostatnio przez International Association of Classification Societies (IACS). Jednym z najważniejszych punktów w tych dokumentach jest wymaganie odnośnie przeprowadzania próby odporności...
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Market Structure and Market Power in Selected Sectors of The Polish Economy Based on COICOP Classification
PublikacjaThis paper present new and simple measures of market structure and market power. Based on the classical models of market structures, where a given structure is determined by the number of enterprises, indexes of degree of monopoly have been estimated, representing an average number of entities per branch. Additionally, market power indexes have been determined as an average revenue per an enterprise in a given branch. This approach...
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Surface water quality assessment by the use of combination of multivariate statistical classification and expert information
PublikacjaThe present study deals with the assessment of surface water quality from an industrial-urban region located in northern Poland near to the city of Gdansk. Concentrations of thirteen chemicals includingtotal polycyclic aromatic hydrocarbons (PAHs), halogenated volatile organic compounds (HVOCs) and major ions in the samples collected at five sampling points during six campaigns were used as variablesthroughout the study. The originality...
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Density-conserving affine continuous cellular automata solving the relaxed density classification problem
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Problem of soil science based classification of land in the context of updating land and building records
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Clinical characteristics of children with MIS-C fulfilling classification criteria for macrophage activation syndrome
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MPEG-7-based low level descriptor effectiveness in the automatic musical sound classification.
PublikacjaCelem referatu jest określenie, które z parametrów opisowych MPEG-7 są najbardziej przydatne w klasyfikacji dźwięków instrumentów muzycznych. Określana jest wysokość dźwięku a następnie wyznaczane są wartości parametrów zawartych w standardzie MPEG-7. Otrzymany wektor parametrów poddawany jest analizie statystycznej w celu wyeliminowania danych nadmiarowych. Do celów automatycznej klasyfikacji i testów zaprojektowano dwa systemy...
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Bimodal classification of English allophones employing acoustic speech signal and facial motion capture
PublikacjaA method for automatic transcription of English speech into International Phonetic Alphabet (IPA) system is developed and studied. The principal objective of the study is to evaluate to what extent the visual data related to lip reading can enhance recognition accuracy of the transcription of English consonantal and vocalic allophones. To this end, motion capture markers were placed on the faces of seven speakers to obtain lip...
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublikacjaRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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Flood Classification in a Natural Wetland for Early Spring Conditions Using Various Polarimetric SAR Methods
PublikacjaAbstract--- One of the major limitations of remote sensing flood detection is the presence of vegetation. Our study focuses on a flood classification using Radarsat-2 Quad-Pol data in a natural floodplain during leafless, dry vegetation (early spring) state. We conducted a supervised classification of a data set composed of nine polarimetric decompositions and Shannon entropy followed by the predictors' importance estimation to...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublikacjaPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
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Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaEvaluation of sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for discerning between the events being in focus and the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe 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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Video Classification Technology in a Knowledge-Vision-Integration Platform for Personal Protective Equipment Detection: An Evaluation
PublikacjaThis 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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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Two-center radial basis function network for classification of soft faults in electronic analog circuits
PublikacjaW pracy zaproponowano specjalizowaną sieć neuronową z dwucentrowymi radialnymi funkcjami bazowymi (TCRB) neuronów w warstwie ukrytej,przeznaczoną do diagnostyki uszkodzeń parametrycznych układów analogowych. Zastosowanie funkcji TCRB pozwala na znaczne zmniejszenie liczby neuronów w warstwie ukrytej, lepsze dopasowanie do słownika uszkodzeń oraz poprawę dokładności klasyfikacji, w porównaniu z dotychczas stosowaną siecią z jednocentrowymi...
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Classification of Thyroid Tumors Based on Mass Spectrometry Imaging of Tissue Microarrays; a Single-Pixel Approach
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A multi-label text message classification method designed for applications in call/contact centre systems
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublikacjaIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublikacjaAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublikacjaDeep 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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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...