LEADER 04047nam 22006375 450 001 9910337849603321 005 20200705191620.0 010 $a3-030-20984-9 024 7 $a10.1007/978-3-030-20984-1 035 $a(CKB)4100000008280565 035 $a(DE-He213)978-3-030-20984-1 035 $a(MiAaPQ)EBC5924106 035 $a(PPN)236522256 035 $a(EXLCZ)994100000008280565 100 $a20190514d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMultimodal Pattern Recognition of Social Signals in Human-Computer-Interaction$b[electronic resource] $e5th IAPR TC 9 Workshop, MPRSS 2018, Beijing, China, August 20, 2018, Revised Selected Papers /$fedited by Friedhelm Schwenker, Stefan Scherer 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (VII, 117 p. 117 illus., 32 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence ;$v11377 311 $a3-030-20983-0 320 $aIncludes bibliographical references and index. 327 $aMulti-Focus Image Fusion with PCA Filters of PCANet -- An Image Captioning Method for Infant Sleeping Environment Diagnosis -- A First-Person Vision Dataset of Office Activities -- Perceptual Judgments to Detect Computer Generated Forged Faces in Social Media -- Combining Deep and Hand-crafted Features for Audio-based Pain Intensity Classification -- Deep Learning Algorithms for Emotion Recognition on Low Power Single Board Computers -- Improving Audio-Visual Speech Recognition Using Gabor Recurrent Neural Networks -- Evolutionary Algorithms for the Design of Neural Network Classifiers for the Classification of Pain Intensity -- Visualizing Facial Expression Features of Pain and Emotion Data. 330 $aThis book constitutes the refereed post-workshop proceedings of the 5th IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2018, held in Beijing, China, in August 2018. The 10 revised papers presented in this book focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition and pain intensity estimation, especially the question how to distinguish between human emotions from pain or stress induced by pain is discussed. 410 0$aLecture Notes in Artificial Intelligence ;$v11377 606 $aArtificial intelligence 606 $aOptical data processing 606 $aComputer communication systems 606 $aUser interfaces (Computer systems) 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 606 $aUser Interfaces and Human Computer Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/I18067 615 0$aArtificial intelligence. 615 0$aOptical data processing. 615 0$aComputer communication systems. 615 0$aUser interfaces (Computer systems). 615 14$aArtificial Intelligence. 615 24$aImage Processing and Computer Vision. 615 24$aComputer Communication Networks. 615 24$aUser Interfaces and Human Computer Interaction. 676 $a004.019 702 $aSchwenker$b Friedhelm$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aScherer$b Stefan$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910337849603321 996 $aMultimodal Pattern Recognition of Social Signals in Human-Computer-Interaction$92511940 997 $aUNINA