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001432588 001__ 1432588
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001432588 019__ $$a1237473441$$a1238206175$$a1241066197$$a1249943411$$a1250096499
001432588 020__ $$a9783030615772$$q(electronic bk.)
001432588 020__ $$a3030615774$$q(electronic bk.)
001432588 020__ $$z9783030615765
001432588 0247_ $$a10.1007/978-3-030-61577-2$$2doi
001432588 035__ $$aSP(OCoLC)1223097335
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001432588 049__ $$aISEA
001432588 050_4 $$aTJ211.49
001432588 08204 $$a629.8/924019$$223
001432588 08204 $$a006.3$$223
001432588 1001_ $$aChen, Luefeng,$$eauthor.
001432588 24510 $$aEmotion recognition and understanding for emotional human-robot interaction systems /$$cLuefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota.
001432588 264_1 $$aCham :$$bSpringer,$$c[2021]
001432588 300__ $$a1 online resource (xi, 247 pages) :$$billustrations
001432588 336__ $$atext$$btxt$$2rdacontent
001432588 337__ $$acomputer$$bc$$2rdamedia
001432588 338__ $$aonline resource$$bcr$$2rdacarrier
001432588 347__ $$atext file
001432588 347__ $$bPDF
001432588 4901_ $$aStudies in computational intelligence ;$$vvolume 926
001432588 504__ $$aIncludes bibliographical references and index.
001432588 5050_ $$aIntroduction -- Multi-modal emotion feature extraction -- Deep sparse autoencoder network for facial emotion recognition -- AdaBoost-knn with direct optimization for dynamic emotion recognition -- Weight-adapted convolution neural network for facial expression recognition -- Two-layer fuzzy multiple random forest for speech emotion recognition -- Two-stage fuzzy fusion based-convolution neural network for dynamic emotion recognition -- Multi-support vector machine based Dempster-Shafer theory for gesture intention understanding -- Three-layer weighted fuzzy support vector regressions for emotional intention understanding -- Dynamic emotion understanding based on two-layer fuzzy fuzzy support vector regression-Takagi-Sugeno model -- Emotion-age-gender-nationality based intention understanding using two-layer fuzzy support vector regression -- Emotional human-robot interaction systems -- Experiments and applications of emotional human-robot.
001432588 506__ $$aAccess limited to authorized users.
001432588 520__ $$aThis book focuses on the key technologies and scientific problems involved in emotional robot systems, such as multimodal emotion recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the design and application examples of emotional HRI systems. Aiming at the development needs of emotional robots and emotional humanrobot interaction (HRI) systems, this book introduces basic concepts, system architecture, and system functions of affective computing and emotional robot systems. With the professionalism of this book, it serves as a useful reference for engineers in affective computing, and graduate students interested in emotion recognition and intention understanding. This book offers the latest approaches to this active research area. It provides readers with the state-of-the-art methods of multimodal emotion recognition, intention understanding, and application examples of emotional HRI systems.
001432588 588__ $$aDescription based on print version record.
001432588 650_0 $$aHuman-robot interaction.
001432588 650_0 $$aRobotics$$xHuman factors.
001432588 650_0 $$aEmotion recognition.
001432588 650_6 $$aInteraction homme-robot.
001432588 650_6 $$aRobotique$$xFacteurs humains.
001432588 650_6 $$aReconnaissance des émotions.
001432588 655_0 $$aElectronic books.
001432588 7001_ $$aWu, Min,$$eauthor.
001432588 7001_ $$aPedrycz, Witold,$$d1953-$$eauthor.
001432588 7001_ $$aHirota, K.$$q(Kaoru),$$eauthor.
001432588 77608 $$iPrint version:$$aChen, Luefeng.$$tEmotion Recognition and Understanding for Emotional Human-Robot Interaction Systems.$$dCham : Springer International Publishing AG, ©2021$$z9783030615765
001432588 830_0 $$aStudies in computational intelligence ;$$vv. 926.
001432588 852__ $$bebk
001432588 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-61577-2$$zOnline Access$$91397441.1
001432588 909CO $$ooai:library.usi.edu:1432588$$pGLOBAL_SET
001432588 980__ $$aBIB
001432588 980__ $$aEBOOK
001432588 982__ $$aEbook
001432588 983__ $$aOnline
001432588 994__ $$a92$$bISE