Isbn: 9786202919708 - human emotion recognition from face images: recognition and retrieval of emotions from facial expression (5 risultati)

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    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202919701 / 9786202919708

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      Da: preigu, Osnabrück, Germaniapreigu

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      Taschenbuch. Condizione: Neu. Human Emotion Recognition from face Images | Recognition and retrieval of emotions from facial expression | K. Prasanthi Jasmine (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202919708 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Okt 2020, 2020

      6202919701 / 9786202919708

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The human emotion recognition from face images based on textural analysis and linear classifier. Automatic facial expression recognition (FER) plays an important role in HCI systems for measuring people's emotions has dominated psychology by linking expressions to a group of basic emotions (i.e., anger, disgust, fear, happiness, sadness, and surprise). The recognition system involves face detection, features extraction and selection and finally classification. The face detection module will be used to obtain face images, which have normalized intensity, are uniform in size and shape and depict only the face region. The optimum features are selected using minimum redundancy maximum relevance algorithm based on mutual information (MI). The mutual information quotient (MIQ) method for feature selection is adopted to select the optimum features. 84 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202919701 / 9786202919708

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      Da: moluna, Greven, Germaniamoluna

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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: JASMINE K.PRASANTHIDr. K. Prasanthi Jasmine is Professor of Department of Electronics and Communication Engineering at Andhra Loyola Institute of Engineering and Technology, Vijayawada, (A.P). She was awarded Ph.D from Andhra Univers.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2020

      6202919701 / 9786202919708

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The human emotion recognition from face images based on textural analysis and linear classifier. Automatic facial expression recognition (FER) plays an important role in HCI systems for measuring people's emotions has dominated psychology by linking expressions to a group of basic emotions (i.e., anger, disgust, fear, happiness, sadness, and surprise). The recognition system involves face detection, features extraction and selection and finally classification. The face detection module will be used to obtain face images, which have normalized intensity, are uniform in size and shape and depict only the face region. The optimum features are selected using minimum redundancy maximum relevance algorithm based on mutual information (MI). The mutual information quotient (MIQ) method for feature selection is adopted to select the optimum features.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Okt 2020, 2020

      6202919701 / 9786202919708

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      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      EUR 39,90

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      Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The human emotion recognition from face images based on textural analysis and linear classifier. Automatic facial expression recognition (FER) plays an important role in HCI systems for measuring people¿s emotions has dominated psychology by linking expressions to a group of basic emotions (i.e., anger, disgust, fear, happiness, sadness, and surprise). The recognition system involves face detection, features extraction and selection and finally classification. The face detection module will be used to obtain face images, which have normalized intensity, are uniform in size and shape and depict only the face region. The optimum features are selected using minimum redundancy maximum relevance algorithm based on mutual information (MI). The mutual information quotient (MIQ) method for feature selection is adopted to select the optimum features.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.