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Wyniki wyszukiwania dla: viseme · parameterization of mouth region · support vector machine · hidden markov model · pattern recognition · audiovisual speech recognition

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Wyniki wyszukiwania dla: viseme · parameterization of mouth region · support vector machine · hidden markov model · pattern recognition · audiovisual speech recognition

  • Versatile pattern recognition system based on Fisher criterion

    Publikacja

    - Rok 2003

    Zaprezentowano 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.

  • Facial emotion recognition using depth data

    Publikacja

    - Rok 2015

    In 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...

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  • Pose classification in the gesture recognition using the linear optical sensor

    Publikacja

    Gesture 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...

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  • Recognition and sensing of anions

    Publikacja

    Molecular 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

    Publikacja

    - Rok 2018

    The 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.

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  • Noise profiling for speech enhancement employing machine learning models

    Publikacja

    - Journal of the Acoustical Society of America - Rok 2022

    This 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...

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  • Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams

    Publikacja

    - Rok 2015

    A 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

    Publikacja

    - Rok 2022

    This 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...

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  • Feature extraction in detection and recognition of graphical objects

    Publikacja

    - Rok 2022

    Detection 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

    Publikacja

    This 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...

  • Emotion Recognition Based on Facial Expressions of Gamers

    This 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...

  • Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition

    Publikacja

    - Biomedical Signal Processing and Control - Rok 2023

    Brain–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....

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  • Automatic sound recognition for security purposes

    Publikacja

    - Rok 2008

    In 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

    Publikacja

    - Rok 2007

    This 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

    Publikacja

    - Rok 2013

    In 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

    Publikacja

    - LECTURE NOTES IN COMPUTER SCIENCE - Rok 2011

    Computer 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

    Publikacja

    - Rok 2013

    Recognizing 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...

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  • Emotion Recognition for Affect Aware Video Games

    In 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

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  • Emotion Recognition and Its Applications

    The 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...

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  • High quality speech codec employing sines+noise+transients model

    A 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...

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  • Emotion Recognition Using Physiological Signals

    Publikacja

    - Rok 2015

    In 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...

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  • Comparison of Language Models Trained on Written Texts and Speech Transcripts in the Context of Automatic Speech Recognition

    Publikacja
    • S. Dziadzio
    • A. Nabożny
    • A. Smywiński-Pohl
    • B. Ziółko

    - Rok 2015

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  • Emotion Recognition from Physiological Channels Using Graph Neural Network

    In 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...

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  • Bimodal Emotion Recognition Based on Vocal and Facial Features

    Emotion 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...

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  • Emotion recognition and its application in software engineering

    In 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...

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  • Systematic Literature Review for Emotion Recognition from EEG Signals

    Researchers 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

    Publikacja

    Researchers 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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  • Analysis of Lombard speech using parameterization and the objective quality indicators in noise conditions

    Publikacja

    - Rok 2018

    The 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

    In 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....

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  • Markov Model of Disease Development and Recovery

    Publikacja

    - Rok 2016

    Markov 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,...

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  • Application of Syntactic Pattern Recognition Approach in Design and Optimisation of Group Machining Systems

    Publikacja
    • M. Siemiatkowski

    - Solid State Phenomena - Rok 2010

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  • Application of Syntactic Pattern Recognition Approach in Design and Optimisation of Group Machining Systems

    Publikacja

    Rozwinięto 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....

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  • Adversarial attack algorithm for traffic sign recognition

    Publikacja

    - MULTIMEDIA TOOLS AND APPLICATIONS - Rok 2022

    Deep 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...

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  • Anion recognition by n,n'-diarylalkanediamides

    Publikacja

    The 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...

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  • Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review

    Publikacja

    - SENSORS - Rok 2022

    The 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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  • AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS

    Publikacja

    Symptoms 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

    This 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...

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  • Accelerometer signal pre-processing influence on human activity recognition

    A 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.

  • From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition

    Publikacja

    Recently 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...

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  • Survival time prognosis under a Markov model of cancer development

    Publikacja

    - Rok 2010

    In 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

    Publikacja

    - Rok 2005

    Artykuł 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...

  • Music Genre Recognition in the Rough Set-Based Environment

    Publikacja

    - Rok 2015

    The aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...

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  • Limitations of Emotion Recognition from Facial Expressions in e-Learning Context

    Publikacja

    The paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...

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  • Spirometry measurement model - the diagnostic purpose support

    the 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...

  • An Attempt to Create Speech Synthesis Model That Retains Lombard Effect Characteristics

    Publikacja

    - Rok 2019

    The speech with the Lombard effect has been extensively studied in the context of speech recognition or speech enhancement. However, few studies have investigated the Lombard effect in the context of speech synthesis. The aim of this paper is to create a mathematical model that allows for retaining the Lombard effect. These models could be used as a basis of a formant speech synthesizer. The proposed models are based on dividing...

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  • Topology recognition and leader election in colored networks

    Publikacja

    Topology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...

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  • Molecular Recognition in Complexes of TRF Proteins with Telomeric DNA

    Publikacja

    Telomeres are specialized nucleoprotein assemblies that protect the ends of linear chromosomes. In humans and many other species, telomeres consist of tandem TTAGGG repeats bound by a protein complex known as shelterin that remodels telomeric DNA into a protective loop structure and regulates telomere homeostasis. Shelterin recognizes telomeric repeats through its two major components known as Telomere Repeat-Binding Factors, TRF1...

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  • Hidden Markov Models for Visual Processing of Marketing Leaflets

    Publikacja

    - Rok 2021

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  • Hand gesture recognition supported by fuzzy rules and Kalman filters

    The paper presents a system based on camera and multimediaprojector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology....

  • Automatic recognition of therapy progress among children with autism

    Publikacja

    - Scientific Reports - Rok 2017

    The article presents a research study on recognizing therapy progress among children with autism spectrum disorder. The progress is recognized on the basis of behavioural data gathered via five specially designed tablet games. Over 180 distinct parameters are calculated on the basis of raw data delivered via the game flow and tablet sensors - i.e. touch screen, accelerometer and gyroscope. The results obtained confirm the possibility...

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