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wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: DATASET FEATURES, DATASET PROFILING VOCABULARIES
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A Triplet-Learnt Coarse-to-Fine Reranking for Vehicle Re-identification
PublikacjaVehicle re-identification refers to the task of matching the same query vehicle across non-overlapping cameras and diverse viewpoints. Research interest on the field emerged with intelligent transportation systems and the necessity for public security maintenance. Compared to person, vehicle re-identification is more intricate, facing the challenges of lower intra-class and higher inter-class similarities. Motivated by deep...
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Methodology of Constructing and Analyzing the Hierarchical Contextually-Oriented Corpora
PublikacjaMethodology of Constructing and Analyzing the Hierarchical structure of the Contextually-Oriented Corpora was developed. The methodology contains the following steps: Contextual Component of the Corpora’s Structure Building; Text Analysis of the Contextually-Oriented Hierarchical Corpus. Main contribution of this study is the following: hierarchical structure of the Corpus provides advanced possibilities for identification of the...
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Selection of Visual Descriptors for the Purpose of Multi-camera Object Re-identification
PublikacjaA comparative analysis of various visual descriptors is presented in this chapter. The descriptors utilize many aspects of image data: colour, texture, gradient, and statistical moments. The descriptor list is supplemented with local features calculated in close vicinity of key points found automatically in the image. The goal of the analysis is to find descriptors that are best suited for particular task, i.e. re-identification...
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Vehicle Detection and Speed Estimation Using Millimetre Wave Radar
PublikacjaThe dataset titled Data from 76- to 81-GHz mmWave Sensor located at S7 road contains data recorded employing an IWR1642 mmWave sensor from Texas Instruments. The data comes from two sessions lasting 24h each. The dataset provides the possibility to perform analyses related to car traffic intensity on one of the carriageways of the motorway heading to the Gdańsk metropolitan area. Based on the gathered data, it is possible to calculate...
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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation
PublikacjaModern data acquisition technologies provide large datasets that are not always necessary in its entirety to properly accomplish the goal of the study. In addition, such datasets are often cumbersome for rational processing, and their processing is time and labour consuming. Therefore, methods that enable to reduce the size of the measurement dataset, such as the generalization of the Digital Terrain Model (DTM) or the reduction...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublikacjaFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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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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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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The OptD-multi method in LiDAR processing
PublikacjaNew and constantly developing technology for acquiring spatial data, such as LiDAR (light detection and ranging), is a source for large volume of data. However, such amount of data is not always needed for developing the most popular LiDAR products: digital terrain model (DTM) or digital surface model. Therefore, in many cases, the number of contained points are reduced in the pre-processing stage. The degree of reduction is determined...
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Style Transfer for Detecting Vehicles with Thermal Camera
PublikacjaIn this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...
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Crack Mouth Opening Displacement for EH36 Shipbuilding Steel Measurements
PublikacjaThe dataset titled EH36 steel for shipbuilding (plate thicnkness 50mm) - CMOD - force record, a0/W = 0.6 contains CMOD (Crack Mouth Opening Displacement) - Force record which is the base for evaluation of fracture toughness of structural steel. Bend specimens witch Bx2B section (B= 50mm), and relative initial crack length a0 / W = 0.60 were used. The test was carried out at ambient temperature in accordance to ISO 12135 standard....
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Exploratory analysis and ranking of analytical procedures for short-chain chlorinated paraffins determination in environmental solid samples
PublikacjaShort-chain chlorinated paraffins are ones of the most recent chemical compounds that have been classified as persistent organic pollutants. They have various applications and are emitted to the environment. Despite the fact, that the content levels of these compounds in the environmental compartments should be monitored, there is still a lack of well-defined and validated analytical procedures, proposed or suggested by the national...
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Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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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...
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Extending touch-less interaction with smart glasses by implementing EMG module
PublikacjaIn this paper we propose to use temporal muscle contraction to perform certain actions. Method: The set of muscle contractions corresponding to one of three actions including “single-click”, “double-click” “click-n-hold” and “non-action” were recorded. After recording certain amount of signals, the set of five parameters was calculated. These parameters served as an input matrix for the neural network. Two-layer feedforward neural...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Viewpoint independent shape-based object classification for video surveillance
PublikacjaA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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Outlier detection method by using deep neural networks
PublikacjaDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Long-Term GNSS Tropospheric Parameters for the Tropics (2001-2018) Derived from Selected IGS Stations
PublikacjaThis paper describes dataset “Tropospheric parameters derived from selected IGS stations in the tropics for the years 2001-2018” contains GNSS-derived zenith tropospheric delay (ZTD), a posteriori corrected zenith wet delay (ZWD), and precipitable water vapour (PWV) time series. These troposphere-related data were estimated for the Jan 2001 – Dec 2018 period for 43 International GNSS Service (IGS) stations located across the global...
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Exploring the Usability and User Experience of Social Media Apps through a Text Mining Approach
PublikacjaThis study aims to evaluate the applicability of a text mining approach for extracting UUX-related issues from a dataset of user comments and not to evaluate the Instagram (IG) app. This study analyses textual data mined from reviews in English written by IG mobile application users. The article’s authors used text mining (based on the LDA algorithm) to identify the main UUX-related topics. Next, they mapped the identified topics...
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Local variability in snow concentrations of chlorinated persistent organic pollutants as a source of large uncertainty in interpreting spatial patterns at all scales
PublikacjaSingle point sampling, a widespread practice in snow studies in remote areas, due to logistical constraints, can present an unquantified error to the final study results. The low concentrations of studied chemicals, such as chlorinated persistent organic pollutants, contribute to the uncertainty. We conducted a field experiment in the Arctic to estimate the error stemming from differences in the composition of snow at short distances...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn 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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Methodology for Processing of 3D Multibeam Sonar Big Data for Comparative Navigation
PublikacjaAutonomous navigation is an important task for unmanned vehicles operating both on the surface and underwater. A sophisticated solution for autonomous non-global navigational satellite system navigation is comparative (terrain reference) navigation. We present a method for fast processing of 3D multibeam sonar data to make depth area comparable with depth areas from bathymetric electronic navigational charts as source maps during...
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Searching for Solvents with an Increased Carbon Dioxide Solubility Using Multivariate Statistics
PublikacjaIonic liquids (ILs) are used in various fields of chemistry. One of them is CO2 capture, a process that is quite well described. The solubility of CO2 in ILs can be used as a model to investigate gas absorption processes. The aim is to find the relationships between the solubility of CO2 and other variables—physicochemical properties and parameters related to greenness. In this study, 12 variables are used to describe a dataset...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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High performance filtering for big datasets from Airborne Laser Scanning with CUDA technology
PublikacjaThere are many studies on the problems of processing big datasets provided by Airborne Laser Scanning (ALS). The processing of point clouds is often executed in stages or on the fragments of the measurement set. Therefore, solutions that enable the processing of the entire cloud at the same time in a simple, fast, efficient way are the subject of many researches. In this paper, authors propose to use General-Purpose computation...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublikacjaIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Standard deviation as the optimization criterion in the OptD method and its influence on the generated DTM
PublikacjaReduction of the measurement dataset is one of the current issues related to constantly developing technologies that provide large datasets, eg. laser scanning. It could seems that presence and evolution of processors computer, increase of hard drive capacity etc. is the solution for development of such large datasets. And in fact it is, however, the “lighter” datasets are easier to work with. Additionally, reduced datasets can...
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MULTI-OBJECTIVE OPTIMIZATION PROBLEM IN THE OptD-MULTI METHOD
PublikacjaNew measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublikacjaThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Using contextual conditional preferences for recommendation taska: a case study in the movie domain
PublikacjaRecommendation engines aim to propose users items they are interested in by looking at the user interaction with a system. However, individual interests may be drastically influenced by the context in which decisions are taken. We present an attempt to model user interests via a set of contextual conditional preferences. We show that usage of proposed preferences gives reasonable values of the accuracy and the precision even when...
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Herbarium of Division of Marine Biology and Ecology as the Primary Basis for Conservation Status Assessments in the Gulf of Gdańsk
PublikacjaThe dataset titled Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE) is a research herbarium encompassing specimens of vascular plants and algae hosted by the Laboratory of Marine Plant Ecology at the University of Gdańsk, Poland. The aim of Herbarium is to preserve marine plant and algae collections mostly from the Gulf of Gdańsk, but the herbarium also holds specimens from other parts of the world.
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublikacjaOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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On Bayesian Tracking and Prediction of Radar Cross Section
PublikacjaWe consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach...
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Minimal Sets of Lefschetz Periods for Morse-Smale Diffeomorphisms of a Connected Sum of g Real Projective Planes
PublikacjaThe dataset titled Database of the minimal sets of Lefschetz periods for Morse-Smale diffeomorphisms of a connected sum of g real projective planes contains all of the values of the topological invariant called the minimal set of Lefschetz periods, computed for Morse-Smale diffeomorphisms of a non-orientable compact surface without boundary of genus g (i.e. a connected sum of g real projective planes), where g varies from 1 to...
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Speech Analytics Based on Machine Learning
PublikacjaIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Application of Multivariate Adaptive Regression Splines (MARSplines) Methodology for Screening of Dicarboxylic Acids Cocrystal Using 1D and 2D Molecular Descriptors
PublikacjaDicarboxylic acids (DiAs) are probably one of the most popular cocrystals formers. Due to the high hydrophilicity and non-toxicity, they are promising solubilizes of active pharmaceutical ingredients (APIs). Although DiAs appear to be highly capable of forming multicomponent crystals with various compounds, some systems reported in the literature are physical mixtures the solid state without forming stable intermolecular complex....
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Surf Zone Currents in the Coastal Zone of the Southern Baltic Sea – a Modelling Approach
PublikacjaNearshore currents in a multi-bar non-tidal coastal zone environment located in the Southern Baltic Sea are studied. Spatiotemporal seaward-directed jets – so-called rip currents – are an important part of the nearshore current system. In previous research, Dudkowska et al. (2020) performed an extended modelling experiment to determine the wave conditions that are conducive to the emergence of rip currents. In this paper, the...
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On Computing Curlicues Generated by Circle Homeomorphisms
PublikacjaThe dataset entitled Computing dynamical curlicues contains values of consecutive points on a curlicue generated, respectively, by rotation on the circle by different angles, the Arnold circle map (with various parameter values) and an exemplary sequence as well as corresponding diameters and Birkhoff averages of these curves. We additionally provide source codes of the Matlab programs which can be used to generate and plot the...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Detection of the Oocyte Orientation for the ICSI Method Automation
PublikacjaAutomation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...