xix, 264 p. Hardcover. Einband besto�en, daher M�ngelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Cognitive intelligence and robotics. Sprache: Englisch. N� de ref. del art�culo: 9645JB

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Human Emotion Recognition from Face Images (Cognitive Intelligence and Robotics)

Dutta, Paramartha; Barman, Asit

Publicado por Springer, 2020

ISBN 10: 9811538824 ISBN 13: 9789811538827

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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America

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Condici�n: New. N� de ref. del art�culo: ABLIING23Apr0412070088818

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Human Emotion Recognition from Face Images

Paramartha Dutta|Asit Barman

Publicado por Springer Singapore, 2020

ISBN 10: 9811538824 ISBN 13: 9789811538827

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Librería: moluna, Greven, Alemania

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Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the novel use of various signatures as effective features for emotion recognitionDiscusses the innovative use of associated stability to evaluate the robustness of the underlying signatureDetails an ext. N� de ref. del art�culo: 353802972

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Human Emotion Recognition from Face Images

Asit Barman

Publicado por Springer Nature Singapore Mrz 2020, 2020

ISBN 10: 9811538824 ISBN 13: 9789811538827

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Buch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression recognition, such as the grid formation, distance signature, shape signature, texture signature, feature selection, classifier design, and the combination of signatures to improve emotion recognition.The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG. The authors present the concept of signatures for different characteristics such as distance and shape texture, and describe the use of associated stability indices as features, supplementing the feature set with statistical parameters such as range, skewedness, kurtosis, and entropy. In addition, they demonstrate that experiments with such feature choices offer impressive results, and that performance can be further improved by combining the signatures rather than using them individually.There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and security in government, public and private agencies. This book offers a valuable resource for researchers working in these areas. 284 pp. Englisch. N� de ref. del art�culo: 9789811538827

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Human Emotion Recognition from Face Images (Cognitive Intelligence and Robotics)

Dutta, Paramartha; Barman, Asit

Publicado por Springer, 2020

ISBN 10: 9811538824 ISBN 13: 9789811538827

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Librería: Ria Christie Collections, Uxbridge, Reino Unido

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Condici�n: New. In. N� de ref. del art�culo: ria9789811538827_new

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Human Emotion Recognition from Face Images

Asit Barman

Publicado por Springer Nature Singapore, Springer Nature Singapore, 2020

ISBN 10: 9811538824 ISBN 13: 9789811538827

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Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Buch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression recognition, such as the grid formation, distance signature, shape signature, texture signature, feature selection, classifier design, and the combination of signatures to improve emotion recognition.The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG. The authors present the concept of signatures for different characteristics such as distance and shape texture, and describe the use of associated stability indices as features, supplementing the feature set with statistical parameters such as range, skewedness, kurtosis, and entropy. In addition, they demonstrate that experiments with such feature choices offer impressive results, and that performance can be further improved by combining thesignatures rather than using them individually.There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and security in government, public and private agencies. This book offers a valuable resource for researchers working in these areas. N� de ref. del art�culo: 9789811538827

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