Wyszukiwarka
Filtry
wszystkich: 10876
-
Katalog
- Publikacje 9191 wyników po odfiltrowaniu
- Czasopisma 90 wyników po odfiltrowaniu
- Konferencje 54 wyników po odfiltrowaniu
- Osoby 213 wyników po odfiltrowaniu
- Wynalazki 1 wyników po odfiltrowaniu
- Projekty 20 wyników po odfiltrowaniu
- Aparatura Badawcza 8 wyników po odfiltrowaniu
- Kursy Online 144 wyników po odfiltrowaniu
- Wydarzenia 12 wyników po odfiltrowaniu
- Dane Badawcze 1143 wyników po odfiltrowaniu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: viseme · parameterization of mouth region · support vector machine · hidden markov model · pattern recognition · audiovisual speech recognition
-
International Journal of Applied Pattern Recognition
Czasopisma -
World Research Journal of Pattern Recognition
Czasopisma -
Uncertainty in emotion recognition
PublikacjaPurpose–The purpose of this paper is to explore uncertainty inherent in emotion recognition technologiesand the consequences resulting from that phenomenon.Design/methodology/approach–The paper is a general overview of the concept; however, it is basedon a meta-analysis of multiple experimental and observational studies performed over the past couple of years.Findings–The mainfinding of the paper might be summarized as follows:...
-
Versatile pattern recognition system based on Fisher criterion
PublikacjaZaprezentowano system rozpoznawania obrazów w postaci bitmap. Zaimplementowany algorytm ekstrakcji cech jest uniwersalny i może być używany do różnych obrazów. Cały system bazuje na kryterium Fishera.
-
A Framework for Training and Testing of Complex Pattern Recognition Systems
PublikacjaW pracy przedstawiono szkielet aplikacji stworzony po to, by uprościć konstruowanie systemów rozpoznawania obrazów oraz zapewnić środowisko testowe umożliwiające ocenę algorytmów przy użyciu dużych zestawów danych. Jasno zdefiniowana architektura wraz z wieloma gotowymi do użycia modułami pozwala skoncentrować się na implementacji najważniejszych algorytmów. Szkielet wspiera tworzenie modułów, który mogą być wielokrotnie używane,...
-
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...
-
Facial emotion recognition using depth data
PublikacjaIn this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...
-
Pose classification in the gesture recognition using the linear optical sensor
PublikacjaGesture sensors for mobile devices, which have a capability of distinguishing hand poses, require efficient and accurate classifiers in order to recognize gestures based on the sequences of primitives. Two methods of poses recognition for the optical linear sensor were proposed and validated. The Gaussian distribution fitting and Artificial Neural Network based methods represent two kinds of classification approaches. Three types...
-
Recognition and sensing of anions
PublikacjaMolecular ion recognition is one of the most intensively studied areas of supramolecular technology. The reason for this is the essential role that ions play in many biological as well as industrial processes. On the other hand, however, it has been proved that ions can have a negative impact on human health and the environment. For these reasons, it is extremly important to develop rapid and simple methods allowing the determination...
-
Integration in Multichannel Emotion Recognition
PublikacjaThe paper concerns integration of results provided by automatic emotion recognition algorithms. It presents both the challenges and the approaches to solve them. Paper shows experimental results of integration. The paper might be of interest to researchers and practitioners who deal with automatic emotion recognition and use more than one solution or multichannel observation.
-
Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
-
PATTERN RECOGNITION LETTERS
Czasopisma -
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...
-
Human emotion recognition with biosignals
PublikacjaThis chapter presents issues in the field of affective computing. Basic preliminary information for the recognition of emotions is given and models of emotions, various ways of evoking emotions, as well as their theoretical foundations are discussed. The particular attention is given to the use of physiological signals in recognizing emotions. This subject is outlined further below by presenting selected biosignals, their relationship...
-
Feature extraction in detection and recognition of graphical objects
PublikacjaDetection and recognition of graphic objects in images are of great and growing importance in many areas, such as medical and industrial diagnostics, control systems in automation and robotics, or various types of security systems, including biometric security systems related to the recognition of the face or iris of the eye. In addition, there are all systems that facilitate the personal life of the blind people, visually impaired...
-
Emotion Recognition Based on Facial Expressions of Gamers
PublikacjaThis article presents an approach to emotion recognition based on facial expressions of gamers. With application of certain methods crucial features of an analyzed face like eyebrows' shape, eyes and mouth width, height were extracted. Afterwards a group of artificial intelligence methods was applied to classify a given feature set as one of the following emotions: happiness, sadness, anger and fear. The approach presented in this...
-
Emotion Recognition Based on Facial Expressions of Gamers
PublikacjaThis article presents an approach to emotion recognition based on facial expressions of gamers. With application of certain methods crucial features of an analysed face like eyebrows' shape, eyes and mouth width, height were extracted. Afterwards a group of artificial intelligence methods was applied to classify a given feature set as one of the following emotions: happiness, sadness, anger and fear.The approach presented in this...
-
Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
-
Automatic sound recognition for security purposes
PublikacjaIn the paper an automatic sound recognition system is presented. It forms a part of a bigger security system developed in order to monitor outdoor places for non-typical audio-visual events. The analyzed audio signal is being recorded from a microphone mounted in an outdoor place thus a non stationary noise of a significant energy is present in it. In the paper an especially designed algorithm for outdoor noise reduction is presented,...
-
Guido: a musical score recognition system
PublikacjaThis paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.
-
Recognition of Hand Drawn Flowcharts
PublikacjaIn this paper the problem of hand drawn flowcharts recognition is presented. There are described two attitudes to this problem: on-line and off-line. A concept of FCE, a system for recognizing and understanding of freehand drawn on-line flow charts on desktop computer and mobile devices is presented. The first experiments with the FCE system and the planes for future are also described.
-
Semantic Integration of Heterogeneous Recognition Systems
PublikacjaComputer perception of real-life situations is performed using a variety of recognition techniques, including video-based computer vision, biometric systems, RFID devices and others. The proliferation of recognition modules enables development of complex systems by integration of existing components, analogously to the Service Oriented Architecture technology. In the paper, we propose a method that enables integration of information...
-
Using Physiological Signals for Emotion Recognition
PublikacjaRecognizing user’s emotions is the promising area of research in a field of human-computer interaction. It is possible to recognize emotions using facial expression, audio signals, body poses, gestures etc. but physiological signals are very useful in this field because they are spontaneous and not controllable. In this paper a problem of using physiological signals for emotion recognition is presented. The kinds of physiological...
-
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Czasopisma -
Emotion Recognition for Affect Aware Video Games
PublikacjaIn this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented
-
Emotion Recognition and Its Applications
PublikacjaThe paper proposes a set of research scenarios to be applied in four domains: software engineering, website customization, education and gaming. The goal of applying the scenarios is to assess the possibility of using emotion recognition methods in these areas. It also points out the problems of defining sets of emotions to be recognized in different applications, representing the defined emotional states, gathering the data and...
-
High quality speech codec employing sines+noise+transients model
PublikacjaA method of high quality wideband speech signal representation employing sines+transients+noise model is presented. The need for a wideband speech coding approach as well as various methods for analysis and synthesis of sines, residual and transient states of speech signal is discussed. The perceptual criterion is applied in the proposed approach during encoding of sines amplitudes in order to reduce bandwidth requirements and...
-
Emotion Recognition Using Physiological Signals
PublikacjaIn this paper the problem of emotion recognition using physiological signals is presented. Firstly the problems with acquisition of physiological signals related to specific human emotions are described. It is not a trivial problem to elicit real emotions and to choose stimuli that always, and for all people, elicit the same emotion. Also different kinds of physiological signals for emotion recognition are considered. A set of...
-
Emotion Recognition from Physiological Channels Using Graph Neural Network
PublikacjaIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
-
Comparison of Language Models Trained on Written Texts and Speech Transcripts in the Context of Automatic Speech Recognition
Publikacja -
Bimodal Emotion Recognition Based on Vocal and Facial Features
PublikacjaEmotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...
-
Emotion recognition and its application in software engineering
PublikacjaIn this paper a novel application of multimodal emotion recognition algorithms in software engineering is described. Several application scenarios are proposed concerning program usability testing and software process improvement. Also a set of emotional states relevant in that application area is identified. The multimodal emotion recognition method that integrates video and depth channels, physiological signals and input devices...
-
Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers 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...
-
Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers 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...
-
Analysis of Lombard speech using parameterization and the objective quality indicators in noise conditions
PublikacjaThe aim of the work is to analyze Lombard speech effect in recordings and then modify the speech signal in order to obtain an increase in the improvement of objective speech quality indicators after mixing the useful signal with noise or with an interfering signal. The modifications made to the signal are based on the characteristics of the Lombard speech, and in particular on the effect of increasing the fundamental frequency...
-
Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublikacjaIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
-
Markov Model of Disease Development and Recovery
PublikacjaMarkov models are commonly used to simulate diseases and allow modeling of multiple health states and outcomes. Starting with the well known Le Bras multistate model (cascading failure model) with time-independent transitions we will see how simple Markov mortality models may be pressed into the service of survival and event history analysis. We will focus on more complex models which will be able to take into account remission,...
-
Application of Syntactic Pattern Recognition Approach in Design and Optimisation of Group Machining Systems
Publikacja -
Application of Syntactic Pattern Recognition Approach in Design and Optimisation of Group Machining Systems
PublikacjaRozwinięto koncepcję budowy zoptymalizowanych struktur systemów wytwarzania grupowego spektrum części z wykorzystaniem modelu analizy syntaktycznej sekwencji operacji ich procesów technologicznych. Określono formułę metryki odległościowej opisu stopnia zróżnicowania marszrut indywidualnych procesów oraz testowano jej skuteczność w aspekcie eksploracji wielowymiarowych danych i klasteryzacji obiektów wg cech wymagań technologicznych....
-
Adversarial attack algorithm for traffic sign recognition
PublikacjaDeep learning suffers from the threat of adversarial attacks, and its defense methods have become a research hotspot. In all applications of deep learning, intelligent driving is an important and promising one, facing serious threat of adversarial attack in the meanwhile. To address the adversarial attack, this paper takes the traffic sign recognition as a typical object, for it is the core function of intelligent driving. Considering...
-
Anion recognition by n,n'-diarylalkanediamides
PublikacjaThe preparation of N,N'-diarylalkanediamides from respective aliphatic dicarboxylic acidesand 4-nitroaniline via microwave-promoted reactions is presented. The most positive effect of microwave irradiation was observed for N,N'-bis(4-nitrophenyl)butanediamide. Anion binding studies on the obtained diamides were carried out in DMSO and acetonitrile using UV-vis and 1H NMR spectroscopy. A mechanism for selective fluoride recognition...
-
Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublikacjaThe 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...
-
AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublikacjaSymptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....
-
Limitations of Emotion Recognition in Software User Experience Evaluation Context
PublikacjaThis paper concerns how an affective-behavioural- cognitive approach applies to the evaluation of the software user experience. Although it may seem that affect recognition solutions are accurate in determining the user experience, there are several challenges in practice. This paper aims to explore the limitations of the automatic affect recognition applied in the usability context as well as...
-
Accelerometer signal pre-processing influence on human activity recognition
PublikacjaA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy.
-
PATTERN RECOGNITION
Czasopisma -
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...
-
Survival time prognosis under a Markov model of cancer development
PublikacjaIn this study we look at a breast cancer data set of women from Pomerania region collected in year 1987-1992 in the Medical University of Gdańsk. We analyze the clinical risk factors in conjunction with Markov model of cancer development. We evaluate Artificial Neural Network (ANN) survival time prediction via a simulation study.
-
Combining visual and acoustic modalities to ease speech recognition by hearing impaired people
PublikacjaArtykuł prezentuje system, którego celem działania jest ułatwienie procesu treningu poprawnej wymowy dla osób z poważnymi wadami słuchu. W analizie mowy wykorzystane zostały parametry akutyczne i wizualne. Do wyznaczenia parametrów wizualnych na podstawie kształtu i ruchu ust zostały wykorzystane modele Active Shape Models. Parametry akustyczne bazują na współczynnikach melcepstralnych. Do klasyfikacji wypowiadanych głosek została...
-
Spirometry measurement model - the diagnostic purpose support
Publikacjathe paper presents a new model of respiratory mechanism based on the spirometry measurements. the spirometry test assesses the efficiency of the lung ventilation. the respiratory system functioning is based on the ventilation mechanism. thus the quality of the lung depends on the quality of lung ventilation. modelling of the respiratory system supports a diagnostic process. the model parameter estimates are obtained on the basis...