Wyszukiwarka
Filtry
wszystkich: 1055
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: named entity recognition
-
Sign Language Recognition Using Convolution Neural Networks
PublikacjaThe objective of this work was to provide an app that can automatically recognize hand gestures from the American Sign Language (ASL) on mobile devices. The app employs a model based on Convolutional Neural Network (CNN) for gesture classification. Various CNN architectures and optimization strategies suitable for devices with limited resources were examined. InceptionV3 and VGG-19 models exhibited negligibly higher accuracy than...
-
A survey of automatic speech recognition deep models performance for Polish medical terms
PublikacjaAmong the numerous applications of speech-to-text technology is the support of documentation created by medical personnel. There are many available speech recognition systems for doctors. Their effectiveness in languages such as Polish should be verified. In connection with our project in this field, we decided to check how well the popular speech recognition systems work, employing models trained for the general Polish language....
-
Sylwester Kaczmarek dr hab. inż.
OsobySylwester Kaczmarek ukończył studia w 1972 roku jako mgr inż. Elektroniki, a doktorat i habilitację uzyskał z technik komutacyjnych i inżynierii ruchu telekomunikacyjnego w 1981 i 1994 roku na Politechnice Gdańskiej. Jego zainteresowania badawcze ukierunkowane są na: sieci IP QoS, sieci GMPLS, sieci SDN, komutację, ruting QoS, inżynierię ruchu telekomunikacyjnego, usługi multimedialne i jakość usług. Aktualnie jego badania skupiają...
-
Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublikacjaThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
-
Contextual Knowledge to Enhance Workplace Hazard Recognition and Interpretation in a Cognitive Vision Platform
PublikacjaThe combination of vision and sensor data together with the resulting necessity for formal representations builds a central component of an autonomous Cyber Physical System for detection and tracking of laborers in workplaces environments. This system must be adaptable and perceive the environment as automatically as possible, performing in a variety of plants and scenes without the necessity of recoding the application for each...
-
JOURNAL OF MOLECULAR RECOGNITION
Czasopisma -
Theory of recognition in a historical perspective. Axel Honneth's Anerkennung: Eine europäische Ideengeschichte
PublikacjaThe article discusses Honneth excursion into the realm of the history of ideas. This time Honneth decides to laser it on the notion of "recognition" in three different cultural areas and three different traditions: French, English, and German. The article discusses Honneth's persepctive and attempts at finding the common thread that would link three aforementioned traditions.
-
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...
-
A review of emotion recognition methods based on keystroke dynamics and mouse movements
PublikacjaThe 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...
-
Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
-
Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublikacjaData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
-
Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublikacjaThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
-
Journal of Pattern Recognition Research
Czasopisma -
Pattern Recognition and Image Analysis
Czasopisma -
A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors
PublikacjaIn recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones,...
-
Applicability of Emotion Recognition and Induction Methods to Study the Behavior of Programmers
PublikacjaRecent studies in the field of software engineering have shown that positive emotions can increase and negative emotions decrease the productivity of programmers. In the field of affective computing, many methods and tools to recognize the emotions of computer users were proposed. However, it has not been verified yet which of them can be used to monitor the emotional states of software developers. The paper describes a study carried...
-
Recognition of environmentally important ions
Publikacja..
-
Comparison of Acoustic and Visual Voice Activity Detection for Noisy Speech Recognition
PublikacjaThe problem of accurate differentiating between the speaker utterance and the noise parts in a speech signal is considered. The influence of utilizing a voice activity detection in speech signals on the accuracy of the automatic speech recognition (ASR) system is presented. The examined methods of voice activity detection are based on acoustic and visual modalities. The problem of detecting the voice activity in clean and noisy...
-
Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
-
EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublikacjaThe problem of video framerate and audio/video synchronization in audio-visual speech recognition is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
-
Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
-
From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
-
Automatic singing quality recognition employing artificial neural networks
PublikacjaCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
-
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...
-
Karolina Zielińska-Dąbkowska dr inż. arch.
OsobyKarolina M. Zielinska-Dabkowska (dr inż. arch., Dipl.-Ing. Arch.[FH]) jest adiunktem na Wydziale Architektury Politechniki Gdańskiej. W roku 2002 ukończyła studia na Wydziale Architektury i Urbanistyki Politechniki Gdańskiej a w 2004 inżynierii architektonicznej na HAWK Hochschule für angewandte Wissenschaft und Kunst Hildesheim w Niemczech. Po studiach pracowała dla kilku firm o światowej renomie w Berlinie, Londynie, Nowym Jorku...
-
A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublikacjaTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
-
Real-time working gas recognition system based on the array of semiconductor gas sensors and portable computer Raspberry PI
PublikacjaThe gas-analyzing systems based on the array of partially selective gas sensors and pattern-recognition techniques are potentially fast and low-cost alternative for other devices, like gas analysers. They give the possibility of recognition the type and the concentration of measured volatile compounds in their working environment. In this work we present the implementation of gas recognition system, in which the signals from an...
-
Unraveling the Interplay between DNA and Proteins: A Computational Exploration of Sequence and Structure-Specific Recognition Mechanisms
PublikacjaMy PhD dissertation focused on DNA-protein interactions and the recognition of specific DNA sequences and structures. I discovered that acidic amino acid residues (Asp/Glu) play a crucial role by exhibiting a preference for cytosine. Their contribution to binding affinity depends on nearby cytosines, balancing electrostatic repulsion with specific interactions. Acidic residues act as negative selectors, discouraging non-cytosine...
-
Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
-
Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams
PublikacjaA system for recognition of threatening acoustic events employing parallel processing on a supercomputing cluster is featured. The methods for detection, parameterization and classication of acoustic events are introduced. The recognition engine is based onthreshold-based detection with adaptive threshold and Support Vector Machine classifcation. Spectral, temporal and mel-frequency descriptors are used as signal features. The...
-
EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublikacjaThe problem of video framerate and audio/video synchronization in audio-visual speech recogni-tion is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
-
Role of cholesterol in substrate recognition by -secretase
Publikacja-Secretase is an enzyme known to cleave multiple substrates within their transmembrane domains, with the amyloid precursor protein of Alzheimer’s Disease among the most prominent examples. The activity of -secretase strictly depends on the membrane cholesterol content, yet the mechanistic role of cholesterol in the substrate binding and cleavage remains unclear. In this work, we used all-atom molecular dynamics simulations to examine...
-
Viruses, cancer and non-self recognition
Publikacja -
Face Recognition: Shape versus Texture
PublikacjaThis paper describes experiments related to the application of well-known techniques of the texture feature extraction (Local Binary Patterns and Gabor filtering) to the problem of automatic face verification. Results of the tests show that simple image normalization strategy based on the eye center detection and a regular grid of fiducial points outperforms the more complicated approach, employing active models that are able to...
-
Balance recognition on the basis of EEG measurement.
PublikacjaAlthough electroencephalography (EEG) is not typically used for verifying the sense of balance, it can be used for analysing cortical signals responsible for this phenomenon. Simple balance tasks can be proposed as a good indicator of whether the sense of balance is acting more or less actively. This article presents preliminary results for the potential of using EEG to balance sensing....
-
Automatic recognition of males and females among web browser users based on behavioural patterns of peripherals usage
PublikacjaPurpose The purpose of this paper is to answer the question whether it is possible to recognise the gender of a web browser user on the basis of keystroke dynamics and mouse movements. Design/methodology/approach An experiment was organised in order to track mouse and keyboard usage using a special web browser plug-in. After collecting the data, a number of parameters describing the users’ keystrokes, mouse movements and clicks...
-
Artur Gańcza dr inż.
OsobyI received the M.Sc. degree from the Gdańsk University of Technology (GUT), Gdańsk, Poland, in 2019. I am currently a Ph.D. student at GUT, with the Department of Automatic Control, Faculty of Electronics, Telecommunications and Informatics. My professional interests include speech recognition, system identification, adaptive signal processing and linear algebra.
-
The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublikacjaThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
-
Examining Feature Vector for Phoneme Recognition / Analiza parametrów w kontekście automatycznej klasyfikacji fonemów
PublikacjaThe aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...
-
International Journal of Applied Pattern Recognition
Czasopisma -
World Research Journal of Pattern Recognition
Czasopisma -
International Journal on Document Analysis and Recognition
Czasopisma -
Determination of toxic gases based on the responses of a single electrocatalytic sensor and pattern recognition techniques
PublikacjaA response from an electrocatalytic gas sensor contains fingerprint information about the type of gas and its concentration. As a result, a single gas sensor can be used for the determination of different gases. However, information about the type of gas and its concentration is hidden in the unique shape of the current–voltage response and it is quite difficult to explore. One of the ways to get precise information about the measured...
-
1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
PublikacjaA network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....
-
Recognition, understanding and aestheticization of freehand drawing flowcharts
PublikacjaIn this paper a concept of FCA, a system for recognizing, understanding and aestheticization of freehand drawing flow charts is described. The system is based on a proposed by the author FlowGram graph grammar describing flow charts drawing. An open format FlowChartML for flow charts description is also proposed. The aestheticization criterion is formulated that allows for automatic beautification of flow charts. First experiments...
-
Vowel recognition based on acoustic and visual features
PublikacjaW artykule zaprezentowano metodę, która może ułatwić naukę mowy dla osób z wadami słuchu. Opracowany system rozpoznawania samogłosek wykorzystuje łączną analizę parametrów akustycznych i wizualnych sygnału mowy. Parametry akustyczne bazują na współczynnikach mel-cepstralnych. Do wyznaczenia parametrów wizualnych z kształtu i ruchu ust zastosowano Active Shape Models. Jako klasyfikator użyto sztuczną sieć neuronową. Działanie systemu...
-
Acylic congener of cucurbituril: synthesis and recognition properties.
PublikacjaZaprezentowano syntezę analogów acyklicznych cucurbiturilu oraz ich zdolności do kompleksowania wybranych 16 amin, dioli, kwasów dikarboksylowych, pochodnych guanidyny oraz pirydyny. Obserwowane tworzenie kompleksów przebiegało około 180 razy słabiej niż dla cucurbiturilu. Wyniki te świadczą o potencjalnych możliwościach zbliżonych do analogów cyklicznych pod względem tworzenia kompleksów i rozpoznawania wyżej wymienionych...
-
Speech recognition system for hearing impaired people.
PublikacjaPraca przedstawia wyniki badań z zakresu rozpoznawania mowy. Tworzony system wykorzystujący dane wizualne i akustyczne będzie ułatwiał trening poprawnego mówienia dla osób po operacji transplantacji ślimaka i innych osób wykazujących poważne uszkodzenia słuchu. Active Shape models zostały wykorzystane do wyznaczania parametrów wizualnych na podstawie analizy kształtu i ruchu ust w nagraniach wideo. Parametry akustyczne bazują na...
-
Gazetteer compression technique based on substructure recognition
PublikacjaAutomaty skończone są najlepszą formą reprezentacji słowników do przetwarzania języka naturalnego. Przedstawiamy nową technikę kompresji, która jest szczególnie użyteczna w stosunku do pewnego rodzaju słowników. Zastępujemy wielokrotnie występujące podstruktury ich niepowtarzalnymi reprezentantami. Do ich znalezienia traktujemy wektor przejść jako tekst i stosujemy technikę kompresji tekstu w stylu Ziv-Lempel, która znajduje powtórzenia...
-
Multimodal Audio-Visual Recognition of Traffic Events
PublikacjaPrzedstawiono demonstrator systemu wykrywania niebezpiecznych zdarzeń w ruchu drogowym oparty na jednoczesnej analizie danych wizyjnych i akustycznych. System jest częścią systemu automatycznego nadzoru bezpieczeństwa. Wykorzystuje on kamery i mikrofony jako źródła danych. Przedstawiono wykorzystane algorytmy - algorytmy rozpoznawania zdarzeń dźwiękowych oraz analizy obrazu. Zaprezentowano wyniki działania algorytmów na przykładzie...