Search results for: ONTOLOGIES , TIME SERIES ANALYSIS , ROADS , EMOTION RECOGNITION , AFFECTIVE COMPUTING , INTERVIEWS , COMPUTATIONAL MODELING - Bridge of Knowledge

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Search results for: ONTOLOGIES , TIME SERIES ANALYSIS , ROADS , EMOTION RECOGNITION , AFFECTIVE COMPUTING , INTERVIEWS , COMPUTATIONAL MODELING

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Search results for: ONTOLOGIES , TIME SERIES ANALYSIS , ROADS , EMOTION RECOGNITION , AFFECTIVE COMPUTING , INTERVIEWS , COMPUTATIONAL MODELING

  • Emotions in Human-Computer Interaction Research Group (EMORG)

    * rozpoznawanie emocji użytkownika (ang. emotion elicitation) * reprezentację informacji o emocjach użytkownika (ang. emotion representation/ affect modelling) i zarządzanie nimi * ekspresję emocji lub reakcję na emocje przez programy np. przez wirtualne postaci (ang. affect expression) * wybrane zastosowania to badanie użyteczności oprogramowania rozszerzone o aspekty emocjonalne * badania wzorców behawioralnych w połączeniu...

  • Grupa zarządzania wiedzą

    Grupa Zarządzania Wiedzą na Politechnice Gdańskiej jest grupą badawczo-rozwojową skupiającą się na obszarach związanych z zarządzaniem wiedzą i informacją. Naszym priorytetem jest opracowanie zestawu narzędzi i metod umożliwiających przetwarzanie i analizowanie dużych ilości informacji przechowywanych w zasobach WWW. Grupa specjalizuje się w ontologicznych metodach reprezentacji i analizy wiedzy, która zapisana jest w sposób ustrukturalizowany...

  • Inteligentne Systemy Interaktywne

    Naturalne interfejsy, umożliwiające inteligentną interakcję człowiek-maszyna z możliwością oddziaływania na możliwie wszystkie zmysły człowieka równocześnie i bez potrzeby jego wcześniejszego szkolenia w zakresie używania typowych urządzeń zewnętrznych komputera, w tym z wykorzystaniem metod automatycznego rozpoznawania i syntezy mowy, biometrii, proaktywnych (samo-wykonywalnych) dokumentów elektronicznych, rozpoznawania emocji...

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Search results for: ONTOLOGIES , TIME SERIES ANALYSIS , ROADS , EMOTION RECOGNITION , AFFECTIVE COMPUTING , INTERVIEWS , COMPUTATIONAL MODELING

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Search results for: ONTOLOGIES , TIME SERIES ANALYSIS , ROADS , EMOTION RECOGNITION , AFFECTIVE COMPUTING , INTERVIEWS , COMPUTATIONAL MODELING

  • Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis

    Most of the research in the field of emotion recognition is based on datasets that contain data obtained during affective computing experiments. However, each dataset is described by different metadata, stored in various structures and formats. This research can be counted among those whose aim is to provide a structural and semantic pattern for affective computing datasets, which is an important step to solve the problem of data...

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  • Investigation of educational processes with affective computing methods

    Publication

    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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  • Affective Learning Manifesto – 10 Years Later

    Publication

    - Year 2014

    In 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....

  • Graph Representation Integrating Signals for Emotion Recognition and Analysis

    Data 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...

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  • Human emotion recognition with biosignals

    Publication

    - Year 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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