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Titlebook: Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction; Third IAPR TC3 Works Friedhelm Schwenker,Stefan Scherer,Lou

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書目名稱Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction
副標(biāo)題Third IAPR TC3 Works
編輯Friedhelm Schwenker,Stefan Scherer,Louis-Philippe
視頻videohttp://file.papertrans.cn/641/640750/640750.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction; Third IAPR TC3 Works Friedhelm Schwenker,Stefan Scherer,Lou
描述This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.
出版日期Conference proceedings 2015
關(guān)鍵詞Audio-visual speech features; Classifier fusion; Complementary models; Cross-domain retrieval; Discrete
版次1
doihttps://doi.org/10.1007/978-3-319-14899-1
isbn_softcover978-3-319-14898-4
isbn_ebook978-3-319-14899-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Conference proceedings 2015ition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.
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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction978-3-319-14899-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/978-3-319-14899-1Audio-visual speech features; Classifier fusion; Complementary models; Cross-domain retrieval; Discrete
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