Neural Information Processing [electronic resource] : 30th International Conference, ICONIP 2023, Changsha, China, November 20-23, 2023, Proceedings, Part IV / edited by Biao Luo, Long Cheng, Zheng-Guang Wu, Hongyi Li, Chaojie Li.
Contributor(s): Luo, Biao [editor.]
| Cheng, Long [editor.] | Wu, Zheng-Guang [editor.] | Li, Hongyi [editor.] | Li, Chaojie [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 14450Publisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edition: 1st ed. 2024.Description: XX, 577 p. 213 illus., 208 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789819980703.Subject(s): Pattern recognition systems | Data mining | Machine learning | Social sciences -- Data processing | Automated Pattern Recognition | Data Mining and Knowledge Discovery | Machine Learning | Computer Application in Social and Behavioral SciencesAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.4 Online resources: Click here to access online
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Springer Nature eBookSummary: The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. .
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The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. .
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