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[null,"1.","Record Nr.",null,"UNISA990002663530203316"]
[null,null,"Autore",null,"SORKIN, Michael"]
[null,null,"Titolo",null,"After the World Trade Center : rethinking New York city / Michael Sorkin and Sharon Zukin editors"]
[null,null,"Pubbl/distr/stampa",null,"Neyw York : Routledge, 2002"]
[null,null,"ISBN",null,"0-415-93479-6"]
[null,null,"Descrizione fisica",null,"XI, 236 p. ; 24 cm"]
[null,null,"Disciplina",null,"711.4097471"]
[null,null,"Soggetti",null,"Pianificazione urbana - New York"]
[{"$nulls":4},"New York World Trade Center"]
[null,null,"Collocazione",null,"XII.2.C. 767(VII E 993)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910647769903321"]
[null,null,"Autore",null,"Hati Avik"]
[null,null,"Titolo",null,"Image co-segmentation / / Avik Hati [and three others]"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer, , [2023]"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"981-19-8570-7"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (231 pages)"]
[null,null,"Collana",null,"Studies in computational intelligence ; ; Volume 1082"]
[null,null,"Disciplina",null,"006.6"]
[null,null,"Soggetti",null,"Image segmentation"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"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."]
[null,null,null,"Sommario/riassunto","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."]