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Record Nr. |
UNINA9910155273703321 |
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Autore |
De Sourav |
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Titolo |
Hybrid Soft Computing for Multilevel Image and Data Segmentation / / by Sourav De, Siddhartha Bhattacharyya, Susanta Chakraborty, Paramartha Dutta |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XIV, 235 p. 99 illus., 39 illus. in color.) |
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Collana |
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Computational Intelligence Methods and Applications, , 2510-1773 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Computational intelligence |
Image processing - Digital techniques |
Computer vision |
Artificial Intelligence |
Computational Intelligence |
Computer Imaging, Vision, Pattern Recognition and Graphics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Image Segmentation: A Review -- Self-supervised Gray Level Image Segmentation Using an Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation Function -- Self-supervised Gray Level Image Segmentation Using Multiobjective Based Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Multiobjective Based Parallel Optimized MUSIG (ParaOptiMUSIG) Activation Function -- Unsupervised Genetic Algorithm Based Automatic Image Segmentation and Data Clustering Technique Validated by Fuzzy Intercluster Hostility Index. |
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Sommario/riassunto |
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This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures. This is a |
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