LEADER 03565nam 2200889z- 450 001 9910619465803321 005 20221025 010 $a3-0365-5200-6 035 $a(CKB)5670000000391616 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/93210 035 $a(oapen)doab93210 035 $a(EXLCZ)995670000000391616 100 $a20202210d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDeep Learning-Based Action Recognition 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (240 p.) 311 08$a3-0365-5199-9 330 $aThe classification of human action or behavior patterns is very important for analyzing situations in the field and maintaining social safety. This book focuses on recent research findings on recognizing human action patterns. Technology for the recognition of human action pattern includes the processing technology of human behavior data for learning, technology of expressing feature values ??of images, technology of extracting spatiotemporal information of images, technology of recognizing human posture, and technology of gesture recognition. Research on these technologies has recently been conducted using general deep learning network modeling of artificial intelligence technology, and excellent research results have been included in this edition. 606 $aHistory of engineering & technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $a3D skeletal 610 $a3D-CNN 610 $aaction recognition 610 $aactivity recognition 610 $aartificial intelligence 610 $aclass regularization 610 $aclass-specific features 610 $aCNN 610 $acontinuous hand gesture recognition 610 $aconvolutional receptive field 610 $adata augmentation 610 $adeep learning 610 $adynamic gesture recognition 610 $aDynamic Hand Gesture Recognition 610 $aembedded system 610 $afeature fusion 610 $afeedforward neural networks 610 $afusion strategies 610 $agesture classification 610 $agesture spotting 610 $agraph convolution 610 $ahand gesture recognition 610 $ahand shape features 610 $ahigh-order feature 610 $ahuman action recognition 610 $ahuman activity recognition 610 $ahuman-computer interaction 610 $ahuman-machine interface 610 $aLong Short-Term Memory 610 $amulti-modal features 610 $amulti-modalities network 610 $amulti-person pose estimation 610 $an/a 610 $apartition pose representation 610 $apartitioned centerpose network 610 $apose estimation 610 $areal-time 610 $aspatio-temporal differential 610 $aspatio-temporal feature 610 $aspatio-temporal image formation 610 $aspatiotemporal activations 610 $aspatiotemporal feature 610 $astacked hourglass network 610 $atransfer learning 615 7$aHistory of engineering & technology 615 7$aTechnology: general issues 700 $aLee$b Hyo Jong$4edt$01320374 702 $aLee$b Hyo Jong$4oth 906 $aBOOK 912 $a9910619465803321 996 $aDeep Learning-Based Action Recognition$93034204 997 $aUNINA