Wyniki wyszukiwania dla: human activity recognition - MOST Wiedzy

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Wyniki wyszukiwania dla: human activity recognition

Wyniki wyszukiwania dla: human activity recognition

  • Network oscillations modulate interictal epileptiform spike rate during human memory

    Publikacja
    • J. Matsumoto
    • M. Stead
    • M. T. Kucewicz
    • A. Matsumoto
    • P. Peters
    • B. Brinkmann
    • J. C. Danstrom
    • S. Goerss
    • W. Marsh
    • F. Meyer
    • G. Worrell

    - Brain: A Journal of Neurology - Rok 2013

    Eleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in...

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  • Robot Eye Perspective in Perceiving Facial Expressions in Interaction with Children with Autism

    The paper concerns automatic facial expression analysis applied in a study of natural “in the wild” interaction between children with autism and a social robot. The paper reports a study that analyzed the recordings captured via a camera located in the eye of a robot. Children with autism exhibit a diverse level of deficits, including ones in social interaction and emotional expression. The aim of the study was to explore the possibility...

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  • Identification of Emotional States Using Phantom Miro M310 Camera

    Publikacja

    The purpose of this paper is to present the possibilities associated with the use of remote sensing methods in identifying human emotional states, and to present the results of the research conducted by the authors in this field. The studies presented involved the use of advanced image analysis to identify areas on the human face that change their activity along with emotional expression. Most of the research carried out in laboratories...

  • IoT for healthcare applications

    Publikacja
    • K. Sayrafian
    • S. J. Ambroziak
    • D. Bajic
    • L. Berbakov
    • L. M. Correia
    • K. Cwalina
    • C. Garcia-pardo
    • G. Gardašević
    • K. Katzis
    • P. Kulakowski
    • K. Turbic

    - Rok 2021

    This chapter summarizes IRACON contributions related to the application of IoT in healthcare. It consists of the following three sections. Section 8.1 presents the measurement campaigns and the related statistical analysis to obtain various channel models for wearable and implantable devices. In addition, the importance of physical human-body phantoms used for channel, Specific Absorption Rate (SAR), and Electromagnetic (EM) exposure...

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  • A new multi-process collaborative architecture for time series classification

    Publikacja

    - KNOWLEDGE-BASED SYSTEMS - Rok 2021

    Time series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...

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  • Occurrence of Surface Active Agents in the Environment

    Due to the specific structure of surfactants molecules they are applied in different areas of human activity (industry, household). After using and discharging from wastewater treatment plants as effluent stream, surface active agents (SAAs) are emitted to various elements of the environment (atmosphere, waters, and solid phases), where they can undergo numerous physic-chemical processes (e.g., sorption, degradation) and freely...

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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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  • 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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  • 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...

  • MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG

    Publikacja
    • A. Kastrau
    • M. Koronowski
    • M. Liksza
    • P. Jasik

    - Rok 2021

    This study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...

  • 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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  • The optimisation of analytical parameters for routine profiling of antioxidants in complex mixture by HPLC coupled post-column derivatisation

    Introduction: The wide application of natural and artificial antioxidants in food, cosmetic and pharmaceutical industry as well as the recognition of the importance of food antioxidants for supporting human health created demand for reliable and industrially applicable methods of determining antioxidative activity. This requirement can be fullfilled with the recently proposed HPLC-post-column derivatisation approach enabling the...

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  • Stable nanoconjugates of transferrin with alloyed quaternary nanocrystals Ag–In–Zn–S as a biological entity for tumor recognition

    Publikacja

    - NANOSCALE - Rok 2018

    One way to limit the negative effects of anti-tumor drugs on healthy cells is targeted therapy employing functionalized drug carriers. Here we present a biocompatible and stable nanoconjugate of transferrin anchored to Ag-In-Zn-S quantum dots modified with 11-mercaptoundecanoic acid (Tf-QD) as a drug carrier versus typical anticancer drug, doxorubicin. Detailed investigations of Tf-QD nanoconjugates without and with doxorubicin...

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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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  • Knowledge representation of motor activity of patients with Parkinson’s disease

    An approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...

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  • Camera angle invariant shape recognition in surveillance systems

    Publikacja

    A method for human action recognition in surveillance systems is described. Problems within this task are discussed and a solution based on 3D object models is proposed. The idea is shown and some of its limitations are talked over. Shape description methods are introduced along with their main features. Utilized parameterization algorithm is presented. Classification problem, restricted to bi-nary cases is discussed. Support vector...

  • Jaroslaw Spychala dr

    Osoby

    Oprócz bardzo dobrego wykształcenia osoba posiada również wieloletnie doświadczenie zawodowe, które jest poświadczeniem tego, że potrafi wykorzystać swoją wiedzę teoretyczną w praktycznych działaniach. Doświadczenie zawodowe jest bardzo bogate i rozbudowane. Ze względu na nabyte całkiem nowe umiejętności zwiększa się atrakcyjność doświadczonego pracownika. Są to między innymi kreatywne myślenie, zorientowanie na cel, odporność...

  • A review of emotion recognition methods based on keystroke dynamics and mouse movements

    Publikacja

    - Rok 2013

    The 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...

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  • Adjusting Game Difficulty by Recreating Behavioral Trees of Human Player Actions

    Publikacja

    - Rok 2013

    This paper presents a proposition of a method for adjusting game difficulty to the current level of player's skills in one-on-one games. The method is based on recognition of human player's actions and recording of those actions in the form of behavioral trees. Such trees are later used to drive behaviors of computer-controlled opponents so that human player has beat hit own strategy and improve on it, to win subsequent games....

  • Language Models in Speech Recognition

    Publikacja

    - Rok 2022

    This chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.

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  • 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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  • The estrogenicity of wastewater samples.

    Dane Badawcze

    The principle of operation of the kit is based on the fact that the tested sample with endocrine activity (containing compounds capable of binding to the human estrogen receptor α, hERα) releases the fluorescently labeled ligand (FluormoneTM ES2) from the receptor-ligand complex, which results in a reduction of the polarization value fluorescence. The...

  • Mining inconsistent emotion recognition results with the multidimensional model

    Publikacja

    - IEEE Access - Rok 2021

    The paper deals with the challenge of inconsistency in multichannel emotion recognition. The focus of the paper is to explore factors that might influence the inconsistency. The paper reports an experiment that used multi-camera facial expression analysis with multiple recognition systems. The data were analyzed using a multidimensional approach and data mining techniques. The study allowed us to explore camera location, occlusions...

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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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  • 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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  • A novel in vivo approach to assess strains of the human abdominal wall under known intraabdominal pressure

    The study concerns mechanical behaviour of a living human abdominal wall. A better mechanical understanding of a human abdominal wall and recognition of its material properties is required to find mechanically compatible surgical meshes to significantly improve the treatment of ventral hernias. A non-invasive methodology, based on in vivo optical measurements is proposed to determine strains of abdominal wall corresponding to...

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  • Uncertainty in emotion recognition

    Purpose–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:...

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  • 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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  • 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,...

  • An electronic nose for quantitative determination of gas concentrations

    Publikacja

    The practical application of human nose for fragrance recognition is severely limited by the fact that our sense of smell is subjective and gets tired easily. Consequen tly, there is considerable need for an instrument that can be a substitution of the human sense of smell. Electronic nose devices from the mid 1980s are used in growing number of applications. They comprise an array of several electrochemical gas sensors...

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  • 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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  • Investigation of educational processes with affective computing methods

    Publikacja

    This paper concerns the monitoring of educational processes with the use of new technologies for the recognition of human emotions. This paper summarizes results from three experiments, aimed at the validation of applying emotion recognition to e-learning. An analysis of the experiments’ executions provides an evaluation of the emotion elicitation methods used to monitor learners. The comparison of affect recognition algorithms...

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  • Toxoplasma gondii recombinant antigens as tools for serodiagnosis of human toxoplasmosis: current status of studies

    Toxoplasma gondii is a parasitic protozoan which is the cause of toxoplasmosis. Although human toxoplasmosis in healthy adults is usually asymptomatic, serious disease can occur in the case of congenital infections and immunocompromised individuals. Furthermore, despite the exact recognition of its etiology, it still presents a diagnostic problem. Diagnosis of toxoplasmosis is mainly based on the results of serological tests detecting...

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  • Rough Sets Applied to Mood of Music Recognition

    Publikacja

    With the growth of accessible digital music libraries over the past decade, there is a need for research into automated systems for searching, organizing and recommending music. Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition...

  • Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks

    Publikacja

    - IEEE Access - Rok 2022

    Object detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...

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  • FEEDB: A multimodal database of facial expressions and emotions

    Publikacja

    - Rok 2013

    In this paper a first version of a multimodal FEEDB database of facial expressions and emotions is presented. The database contains labeled RGB-D recordings of people expressing a specific set of expressions that have been recorded using Microsoft Kinect sensor. Such a database can be used for classifier training and testing in face recognition as well as in recognition of facial expressions and human emotions. Also initial experiences...

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  • Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition

    The 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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  • 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...

  • Voice command recognition using hybrid genetic algorithm

    Publikacja

    Abstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...

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  • Automatic recognition of males and females among web browser users based on behavioural patterns of peripherals usage

    Publikacja

    - Internet Research - Rok 2016

    Purpose 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...

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  • 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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  • 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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  • Myrosinase activity in different plant samples; optimisation of measurement conditions for spectrophotometric and pH-stat methods

    Myrosinase found in Brassicaceae plants, is the enzyme responsible for hydrolysis of glucosinolates. As a result a variety of biologically active metabolites are liberated, whose importance in crop protection and especially in cancer chemoprevention is rapidly gaining recognition. The growing practical application of glucosinolate degradation products requires that sensitive and reliable methods of myrosinase activity determination...

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  • Examining Influence of Distance to Microphone on Accuracy of Speech Recognition

    The problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...

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  • Dependable Integration of Medical Image Recognition Components

    Computer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....

  • Agnieszka Landowska dr hab. inż.

    Ukończyła studia na dwóch kierunkach: Finanse i bankowość na Uniwersytecie Gdańskim oraz Informatyka na WETI Politechniki Gdańskiej. Od 2000 roku jest związana z Politechniką Gdańską. W 2006 roku uzyskała stopień doktora w dziedzinie nauk technicznych, a w roku 2019 stopień doktora habilitowanego. Aktualnie jej praca naukowa dotyczy zagadnień interakcji człowiek-komputer oraz informatyki afektywnej (ang. affective computing), która...

  • 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...

  • Robust and Efficient Machine Learning Algorithms for Visual Recognition

    Publikacja

    - Rok 2022

    In visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...

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  • Towards Emotion Acquisition in IT Usability Evaluation Context

    Publikacja

    - Rok 2015

    The paper concerns extension of IT usability studies with automatic analysis of the emotional state of a user. Affect recognition methods and emotion representation models are reviewed and evaluated for applicability in usability testing procedures. Accuracy of emotion recognition, susceptibility to disturbances, independence on human will and interference with usability testing procedures are...

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  • Genetic programming extension to APF-based monocular human body pose estimation

    New method of the human body pose estimation based on a single camera 2D observation is presented, aimed at smart surveillance related video analysis and action recognition. It employs 3D model of the human body, and genetic algorithm combined with annealed particle filter for searching the global optimum of model state, best matching the object's 2D observation. Additionally, new motion cost metric is employed, considering current...

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