LEADER 02653nam 2200469 450 001 9910647769903321 005 20230508212501.0 010 $a981-19-8570-7 024 7 $a10.1007/978-981-19-8570-6 035 $a(MiAaPQ)EBC7191152 035 $a(Au-PeEL)EBL7191152 035 $a(CKB)26089741300041 035 $a(DE-He213)978-981-19-8570-6 035 $a(PPN)26820490X 035 $a(EXLCZ)9926089741300041 100 $a20230508d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aImage co-segmentation /$fAvik Hati [and three others] 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer,$d[2023] 210 4$dİ2023 215 $a1 online resource (231 pages) 225 1 $aStudies in computational intelligence ;$vVolume 1082 311 08$aPrint version: Hati, Avik Image Co-Segmentation Singapore : Springer,c2023 9789811985690 327 $aIntroduction -- Survey of Image Co-segmentation -- Mathematical Background -- Co-segmentation using a Classification Framework -- Use of Maximum Common Subgraph Matching -- Maximally Occurring Common Subgraph Matching -- Co-segmentation using Graph Convolutional Neural Network -- Use of a Conditional Siamese Convolutional Network -- Few-shot Learning for Co-segmentation -- Conclusions. 330 $aThis book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder?decoder network, meta-learning, conditional variational encoder?decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning. 410 0$aStudies in computational intelligence ;$vVolume 1082. 606 $aImage segmentation 615 0$aImage segmentation. 676 $a006.6 700 $aHati$b Avik$01277954 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910647769903321 996 $aImage co-segmentation$93364208 997 $aUNINA