1 option
Neural Information Processing : 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part I / edited by Haiqin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, Irwin King.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 12532
- Theoretical Computer Science and General Issues, 2512-2029 ; 12532
- Language:
- English
- Subjects (All):
- Pattern recognition systems.
- Machine learning.
- Computer networks.
- Application software.
- Automated Pattern Recognition.
- Machine Learning.
- Computer Communication Networks.
- Computer and Information Systems Applications.
- Local Subjects:
- Automated Pattern Recognition.
- Machine Learning.
- Computer Communication Networks.
- Computer and Information Systems Applications.
- Physical Description:
- 1 online resource (XXVI, 813 pages) : 112 illustrations
- Edition:
- 1st ed. 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually.The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The first volume, LNCS 12532, is organized in topical sections on human-computer interaction; image processing and computer vision; natural language processing.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-63830-6
- 9783030638306
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.