01100nam--2200361---450-99000266353020331620060124120253.00-415-93479-6000266353USA01000266353(ALEPH)000266353USA0100026635320050927d2002----km-y0itay0103----baengGBy|||z|||001yyAfter the World Trade Centerrethinking New York cityMichael Sorkin and Sharon Zukin editorsNeyw YorkRoutledge2002XI, 236 p.24 cmPianificazione urbanaNew YorkNew YorkWorld Trade Center711.4097471SORKIN,Michael34187ZUKIN,Sharon128264ITsalbcISBD990002663530203316XII.2.C. 767(VII E 993)182458 L.M.VII E00182752BKUMACHIARA9020050927USA011210COPAT59020060124USA011202After the World Trade Center1004969UNISA02653nam 2200469 450 991064776990332120230508212501.0981-19-8570-710.1007/978-981-19-8570-6(MiAaPQ)EBC7191152(Au-PeEL)EBL7191152(CKB)26089741300041(DE-He213)978-981-19-8570-6(PPN)26820490X(EXLCZ)992608974130004120230508d2023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierImage co-segmentation /Avik Hati [and three others]1st ed. 2023.Singapore :Springer,[2023]©20231 online resource (231 pages)Studies in computational intelligence ;Volume 1082Print version: Hati, Avik Image Co-Segmentation Singapore : Springer,c2023 9789811985690 Introduction -- 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.This 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.Studies in computational intelligence ;Volume 1082.Image segmentationImage segmentation.006.6Hati Avik1277954MiAaPQMiAaPQMiAaPQBOOK9910647769903321Image co-segmentation3364208UNINA01132nam 2200385 450 991015617910332120230810001615.01-63322-372-8(CKB)3710000000985411(MiAaPQ)EBC4772369(EXLCZ)99371000000098541120170117h20172017 uy 1engurcnu||||||||rdacontentrdamediardacarrierThe itsy bitsy spider classic nursery rhymes retold /Joe Rhatigan ; illustrated by Farias CarolinaLake Forest, California :MoonDance Press,2017.©20171 online resource (38 pages) color illustrationsClassic Nursery Rhymes Retold1-63322-160-1 Nursery rhymesJuvenile fictionNursery rhymes813.54Rhatigan Joe1379460Carolina FariasMiAaPQMiAaPQMiAaPQBOOK9910156179103321The itsy bitsy spider3419204UNINA