LEADER 04152nam 2201009z- 450 001 9910595077003321 005 20240301154507.0 035 $a(CKB)5680000000080756 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/92049 035 $a(EXLCZ)995680000000080756 100 $a20202209d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence for Multimedia Signal Processing 210 $aBasel$cMDPI Books$d2022 215 $a1 electronic resource (212 p.) 311 $a3-0365-4966-8 311 $a3-0365-4965-X 330 $aArtificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three years to improve image, video, speech, and other data compression efficiency in areas related to MPEG media processing technology. Additionally, technologies such as media creation, processing, editing, and creating scenarios are very important areas of research in multimedia processing and engineering. This book contains a collection of some topics broadly across advanced computational intelligence algorithms and technologies for emerging multimedia signal processing as: Computer vision field, speech/sound/text processing, and content analysis/information mining. 606 $aTechnology: general issues$2bicssc 606 $aHistory of engineering & technology$2bicssc 610 $ahuman-height estimation 610 $adepth video 610 $adepth 3D conversion 610 $aartificial intelligence 610 $aconvolutional neural networks 610 $adeep neural network 610 $aconvolutional neural network 610 $aenvironmental sound recognition 610 $afeature combination 610 $amultimodal joint representation 610 $acontent curation social networks 610 $adifferent recommend tasks 610 $acontent based recommend systems 610 $ascene/place classification 610 $asemantic segmentation 610 $adeep learning 610 $aweighting matrix 610 $aspeech enhancement 610 $agenerative adversarial network 610 $arelativistic GAN 610 $alightweight neural network 610 $asingle image super-resolution 610 $aimage enhancement 610 $aimage restoration 610 $aresidual dense networks 610 $avisual sentiment analysis 610 $asentiment classification 610 $agraph convolutional networks 610 $agenerative adversarial networks 610 $atraffic surveillance image processing 610 $aimage de-raining 610 $afluency evaluation 610 $aspeech recognition 610 $adata augmentation 610 $avariational autoencoder 610 $aspeech conversion 610 $aheartbeat classification 610 $aconvolutional neural network (CNN) 610 $acanonical correlation analysis (CCA) 610 $aIndian Sign Language (ISL) 610 $anatural language processing 610 $aavatar 610 $asign movement 610 $acontext-free grammar 610 $aobject detection 610 $alogical story unit detection (LSU) 610 $aobject re-ID 610 $acomputer vision 610 $aimage processing 610 $asingle image artifacts reduction 610 $adense networks 610 $aresidual networks 610 $achannel attention networks 615 7$aTechnology: general issues 615 7$aHistory of engineering & technology 700 $aKim$b Byung-Gyu$4edt$0761212 702 $aJun$b Dongsan$4edt 702 $aKim$b Byung-Gyu$4oth 702 $aJun$b Dongsan$4oth 906 $aBOOK 912 $a9910595077003321 996 $aArtificial Intelligence for Multimedia Signal Processing$93039267 997 $aUNINA