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Record Nr. |
UNISA996547948703316 |
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Autore |
Orjuela-Cañón Alvaro David |
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Titolo |
Applications of computational intelligence : 5th IEEE Colombian conference, ColCACI 2022, Cali, Colombia, July 27-29, 2022, revised selected papers / / Alvaro David Orjuela-Cañón [and three others] |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023] |
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©2023 |
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ISBN |
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9783031297830 |
9783031297823 |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (xi, 129 pages) : illustrations |
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Collana |
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Communications in Computer and Information Science, , 1865-0937 ; ; 1746 |
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Disciplina |
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Soggetti |
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Computational intelligence |
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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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Design of a segmentation and classification system for seed detection based on pixel intensity thresholds and convolutional neural networks -- Classification of Focused Perturbations Using Time-Variant Functional Connectivity with rs-fmri -- Escherichia coli: Analysis of Features for Protein Localization Classification employing Fusion Data -- Artificial Bee Colony-Based Dynamic Sliding Mode Controller for Integrating Processes with Inverse Response and Deadtime -- Optimizing a Dynamic Sliding Mode Controller with Bio-Inspired Methods: A Comparison -- A robust controller based on LAMDA and Smith Predictor applied to a system with dominant time delay -- Recursive neural networks tuned with a genetic algorithm for the prediction of the Bancolombia stock. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the 5th IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022, held in Cali, Colombia during July 27–29, 2022. The 7 extended papers included in this book were carefully reviewed and selected from 38 submissions. They were organized in topical sections as follows: Design of a segmentation and classification system for seed detection based on pixel intensity thresholds and convolutional neural networks. |
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