LEADER 03593nam 22005535 450 001 9910150447003321 005 20200630091115.0 010 $a3-319-47223-2 024 7 $a10.1007/978-3-319-47223-2 035 $a(CKB)3710000000943225 035 $a(DE-He213)978-3-319-47223-2 035 $a(MiAaPQ)EBC4742103 035 $a(PPN)197141242 035 $a(EXLCZ)993710000000943225 100 $a20161112d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHybrid Soft Computing for Image Segmentation /$fedited by Siddhartha Bhattacharyya, Paramartha Dutta, Sourav De, Goran Klepac 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (XVI, 321 p. 162 illus., 87 illus. in color.) 311 $a3-319-47222-4 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aHybrid Soft Computing Techniques for Image Segmentation: Fundamentals and Applications -- Enhanced Rough-Fuzzy C-Means Algorithm for Image Segmentation -- Intuitionistic Fuzzy C-means Clustering Algorithm for Brain Image Segmentation -- Automatic Segmentation Approaches -- Modified Level Set Segmentation -- Fuzzy Deformable Models for 3D Segmentation of Brain Structures -- Rough Sets for Probabilistic Model Based Image Segmentation -- Segmentation of Cerebral Images. . 330 $aThis book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization. The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence. 606 $aArtificial intelligence 606 $aComputational intelligence 606 $aOptical data processing 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 615 0$aArtificial intelligence. 615 0$aComputational intelligence. 615 0$aOptical data processing. 615 14$aArtificial Intelligence. 615 24$aComputational Intelligence. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 676 $a006.3 702 $aBhattacharyya$b Siddhartha$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDutta$b Paramartha$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDe$b Sourav$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKlepac$b Goran$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910150447003321 996 $aHybrid Soft Computing for Image Segmentation$91963598 997 $aUNINA