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Search results for: KSVM
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Visual Lip Contour Detection for the Purpose of Speech Recognition
PublicationA method for visual detection of lip contours in frontal recordings of speakers is described and evaluated. The purpose of the method is to facilitate speech recognition with visual features extracted from a mouth region. Different Active Appearance Models are employed for finding lips in video frames and for lip shape and texture statistical description. Search initialization procedure is proposed and error measure values are...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Viewpoint independent shape-based object classification for video surveillance
PublicationA 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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Audio-visual surveillance system for application in bank operating room
PublicationAn audio-visual surveillance system able to detect, classify and to localize acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of acoustic...
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Processing of acoustical data in a multimodal bank operating room surveillance system
PublicationAn automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublicationOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Personal bankruptcy prediction using machine learning techniques
PublicationIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...
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Rozpoznawanie chorób układu pokarmowego z wykorzystaniem technik sztucznej inteligencji
PublicationCelem pracy jest przedstawienie i ocena algorytmów rozpoznawania chorób w filmach endoskopowych pod kątem możliwości ich zastosowania do budowy systemów automatycznego wykrywania chorób dla rzeczywistego wspomagania badań lekarskich. Porównano efektywność najnowszych algorytmów poprzez pomiar ich skuteczności w zaawansowanym środowisku testowym, zbudowanym w oparciu o materiały z filmów endoskopowych, opracowane we współpracy z...
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Subspace Algorithms for Face Verification
PublicationW rzeczywistych zastosowaniach problem weryfikacji wydaje się ważniejszy od klasyfikacji. Na ogół dysponujemy jedynie niewielkim zbiorem obrazów uczących reprezentujących daną osobę, a naszym zadaniem jest podjęcie decyzji odnośnie tego, czy nowo pozyskana fotografia jest do nich wystarczająco podobna - bez użycia oddzielnego zbioru przykładów negatywnych. W takim przypadku uzasadnione wydaje się zastosowanie metody podprzestrzeni,...
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Camera Orientation-Independent Parking Events Detection
PublicationThe paper describes the method for detecting precise position and time of vehicles parking in a parking lot. This task is trivial in case of favorable camera orientation but gets much more complex when an angle between the camera viewing axis and the ground is small. The method utilizes background subtraction and object tracking algorithms for detecting moving objects in a video stream. Objects are classified into vehicles and...
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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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A Direct Modulation for Matrix Converters based on the Onecycle Atomic operation developed in Verilog HDL.
PublicationThis paper presents a fast direct Pulse Width Modulation (PWM) algorithm for the Conventional Matrix Converters (CMC) developed in Verilog Hardware Description language (HDL). All PWM duty cycle calculations are performed in one cycle by an atomic operation designed as a digital module using FPGA basic blocks. The algorithm can be extended to any number of output phase. The improved version of the discontinuous Direct Analytic...
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Cross-validation for triplets of HRV and BPV indices based on ordinal patterns in differentiating OSA patients from healthy controls
Open Research DataResults of cross-validation for triplets of HRV and BPV indices based on ordinal patterns, as described in the paper “Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate–blood pressure coupling quantified by entropy-based indices” by P. Pilarczyk, G. Graff, J.M. Amigó, K. Tessmer, K. Narkiewicz, B. Graff.
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Cross-validation for triplets of classical HRV and BPV indices in differentiating OSA patients from healthy controls
Open Research DataResults of cross-validation for triplets of classical HRV and BPV indices, as described in the paper “Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate–blood pressure coupling quantified by entropy-based indices” by P. Pilarczyk, G. Graff, J.M. Amigó, K. Tessmer, K. Narkiewicz, and B. Graff.
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Liveness measurements using optical flow for biometric person authentication
PublicationAutomatyczne rozpoznawanie twarzy jest jedną z najpopularniejszych technik biometrycznych, jednak nawet najdokładniejsze algorytmy identyfikacji okażą się bezużyteczne, jeśli będzie można je oszukać, np. używając zdjęcia zamiast rzeczywistej osoby. Dlatego też odpowiedni pomiar żywotności jest niezwykle istotny. W pracy zaprezentowano metodę, która jest w stanie rozróżnić pomiędzy sekwencjami wideo pokazującymi żywe osoby oraz...
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Rapid Evaluation of Poultry Meat Shelf Life Using PTR-MS
PublicationThe use of proton transfer reaction mass spectrometry (PTR-MS) for freshness classification of chicken and turkey meat samples was investigated. A number of volatile organic compounds (VOCs) were selected based on the correlation (> 95%) of their concentration during storage at 4 °C over a period of 5 days with the results of the microbial analysis. In order to verify if the selected compounds are not sample-specific, a number...
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Paremetrization of sounds for recognizing hazarodus events
PublicationNowoczesne systemy monitoringu działają na zasadzie automatycznego wykrywania niebezpiecznych zdarzeń na podstawie analizy obrazu z kamer i dźwięku z mikrofonów. W niniejszej publikacji skupiono się na pierwszym etapie rozpoznawania zdarzeń dźwiękowych, jakim jest parametryzacja dźwięku. Podstawą do skutecznego działania systemu jest znalezienie parametrów, których zmienność najlepiej odzwierciedla cechy charakterystyczne dźwięku...
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Automatyczna klasyfikacja artykułów Wikipedii
PublicationWikipedia- internetowa encyklopedia do organizacji artykułów wykorzystuje system kategorii. W chwili obecnej proces przypisywania artykułu do odpowiednich kategorii tematycznych realizowany jest ręcznie przez jej edytorów. Zadanie to jest czasochłonne i wymaga wiedzy o strukturze Wikiedii. Ręczna kategoryzacja jest również podatna na błędy wynikające z faktu, że przyporządkowanie artykułu don kategorii odbywa się w oparciu o arbitralną...
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Rozpoznawanie dynamicznych i statycznych gestów rąk w zastosowaniu do sterowania aplikacjami komputerowymi
PublicationW referacie przedstawiono interfejs, metody oraz algorytmy sterowania komputerem za pomocą dynamicznych i statycznych gestów rąk. Komponentami opracowanego rozwiązania są komputer klasy PC wraz z opracowanym interfejsem i oprogramowaniem, kamera internetowa oraz projektor multimedialny. Gesty rozpoznawane są w procesie analizy obrazu wizyjnego pozyskanego z kamery internetowej przymocowanej do projektora oraz analizy obrazu wyświetlanego...
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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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Detection of Denatonium Benzoate (Bitrex) Remnants in Noncommercial Alcoholic Beverages by Raman Spectroscopy
PublicationIllegal alcoholic beverages are often introduced into market using cheap technical alcohol, which is contaminated by denatonium benzoate (Bitrex) of very small concentration. Bitrex is the most bitter chemical compound and has to be removed before alcohol consumption. The home-made methods utilize sodium hypochlorite to disintegrate particles of denatonium benzoate in alcohol and to remove bitter taste before trading. In this experimental...
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Sleep Apnea Detection by Means of Analyzing Electrocardiographic Signal
PublicationObstructive sleep apnea (OSA) is a condition of cyclic, periodic ob-struction (stenosis) of the upper respiratory tract. OSA could be associated with serious cardiovascular problems, such as hypertension, arrhythmias, hearth failure or peripheral vascular disease. Understanding the way of connection between OSA and cardiovascular diseases is important to choose proper treatment strategy. In this paper, we present a method for integrated...
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ANALIZA PARAMETRÓW SYGNAŁU MOWY W KONTEKŚCIE ICH PRZYDATNOŚCI W AUTOMATYCZNEJ OCENIE JAKOŚCI EKSPRESJI ŚPIEWU
PublicationPraca dotyczy podejścia do parametryzacji w przypadku klasyfikacji emocji w śpiewie oraz porównania z klasyfikacją emocji w mowie. Do tego celu wykorzystano bazę mowy i śpiewu nacechowanego emocjonalnie RAVDESS (Ryerson Audio-Visual Database of Emotional Speech and Song), zawierającą nagrania profesjonalnych aktorów prezentujących sześć różnych emocji. Następnie obliczono współczynniki mel-cepstralne (MFCC) oraz wybrane deskryptory...
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...
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Buzz-based recognition of the honeybee colony circadian rhythm
PublicationHoneybees are one of the highly valued pollinators. Their work as individuals is appreciated for crops pollination and honey production. It is believed that work of an entire bee colony is intense and almost continuous. The goal of the work presented in this paper is identification of bees circadian rhythm with a use of sound-based analysis. In our research as a source of information on bee colony we use their buzz that have been...
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Adam Władziński
PeopleAdam Władziński, a PhD Candidate at Gdansk University of Technology, specializes in Biomedical Engineering with a focus on machine learning for image processing and blockchain technology. Holding a BEng and MSc in Electronics, Adam Władziński has developed a keen interest in applying advanced computational techniques to biological systems. During their master’s program, Adam Władziński explored laser spectroscopy, building a database...
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Further developments of parameterization methods of audio stream analysis for secuirty purposes
PublicationThe paper presents an automatic sound recognition algorithm intended for application in an audiovisual security monitoring system. A distributed character of security systems does not allow for simultaneous observation of multiple multimedia streams, thus an automatic recognition algorithm must be introduced. In the paper, a module for the parameterization and automatic detection of audio events is described. The spectral analyses...
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Histogram of Oriented Gradients with Cell Average Brightness for Human Detection
PublicationA modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite 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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Portable Electronic Nose Based on Electrochemical Sensors for Food Quality Assessment
PublicationThe steady increase in global consumption puts a strain on agriculture and might lead to a decrease in food quality. Currently used techniques of food analysis are often labour-intensive and time-consuming and require extensive sample preparation. For that reason, there is a demand for novel methods that could be used for rapid food quality assessment. A technique based on the use of an array of chemical sensors for holistic analysis...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublicationWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublicationThe automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublicationStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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Przetwarzanie sygnałów i obrazów, WIMiO, II st., Mechatronika sem.02 - 22/23 (PG_00057031)
e-Learning CoursesCelem przedmiotu jest nabycie wiedzy w zakresie zaawansowanych metod przetwarzania i analizy sygnałów i obrazów cyfrowych. Zakres obejmuje zagadnienia dotyczące filtracji cyfrowej sygnałów i obrazów (w tym próbkowanie nierównomierne), analiza widmowa i estymacja gęstości widmowej mocy, widma wyższych rzędów, filtr Wienera i Kalmana, liniowa i nieliniowa filtracja adaptacyjne, analiza czasowo-częstotliwościowa (STFT, falkowa), metody...
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Zaawansowane Techniki Przetwarzania Sygnału - Nowy kopiuj 3
e-Learning CoursesPodstawowe pojęcia dotyczące filtracji cyfrowej (w tym próbkowanie nierównomierne), analiza widmowa (estymacja gęstości widmowej mocy, widma wyższych rzędów), zjawisko rezonansu stochastycznego, filtr Wienera i Kalmana, liniowa i nieliniowa filtracja adaptacyjne, analiza czasowo-częstotliwościowa, metody odszumiania sygnałów, metody regresji i detekcji według algorytmów PCA i SVM, metody kodowania sygnałów audio i video, modem...
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Zaawansowane Techniki Przetwarzania Sygnału - r.akad 2024/25
e-Learning CoursesPodstawowe pojęcia dotyczące filtracji cyfrowej (w tym próbkowanie nierównomierne), analiza widmowa (estymacja gęstości widmowej mocy, widma wyższych rzędów), zjawisko rezonansu stochastycznego, filtr Wienera i Kalmana, liniowa i nieliniowa filtracja adaptacyjne, analiza czasowo-częstotliwościowa, metody odszumiania sygnałów, metody regresji i detekcji według algorytmów PCA i SVM, metody kodowania sygnałów audio i video, modem...
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Przetwarzanie sygnałów i obrazów, WIMiO, II st., Mechatronika sem.02 - 23/24 (PG_00057031)
e-Learning CoursesCelem przedmiotu jest nabycie wiedzy w zakresie zaawansowanych metod przetwarzania i analizy sygnałów i obrazów cyfrowych. Zakres obejmuje zagadnienia dotyczące filtracji cyfrowej sygnałów i obrazów (w tym próbkowanie nierównomierne), analiza widmowa i estymacja gęstości widmowej mocy, widma wyższych rzędów, filtr Wienera i Kalmana, liniowa i nieliniowa filtracja adaptacyjne, analiza czasowo-częstotliwościowa (STFT, falkowa), metody...
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Przetwarzanie sygnałów i obrazów, WIMiO, II st., Mechatronika sem.02 - 24/25 (PG_00057031)
e-Learning CoursesCelem przedmiotu jest nabycie wiedzy w zakresie zaawansowanych metod przetwarzania i analizy sygnałów i obrazów cyfrowych. Zakres obejmuje zagadnienia dotyczące filtracji cyfrowej sygnałów i obrazów (w tym próbkowanie nierównomierne), analiza widmowa i estymacja gęstości widmowej mocy, widma wyższych rzędów, filtr Wienera i Kalmana, liniowa i nieliniowa filtracja adaptacyjne, analiza czasowo-częstotliwościowa (STFT, falkowa), metody...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Visual Features for Endoscopic Bleeding Detection
PublicationAims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...
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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
PublicationThis 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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Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublicationAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
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Time window based features extraction from temperature modulated gas sensors for prediction of ammonia concentration
PublicationElectronic gas recognition systems, in literature commonly referred as electronic noses, enable the recognition of a type and a concentration of various volatile compounds. Typical electronic gas-analyzing device consists of four main elements, namely, gas delivery subsystem, an array of gas sensors, data acquisition and power supply circuits and data analysis software. The commercially available metal-oxide TGS sensors are widely...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...