TY  - GEN
N2  - The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 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 11301, is organized in topical sections on deep neural networks, convolutional neural networks, recurrent neural networks, and spiking neural networks.
DO  - 10.1007/978-3-030-04167-0
DO  - doi
AB  - The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 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 11301, is organized in topical sections on deep neural networks, convolutional neural networks, recurrent neural networks, and spiking neural networks.
T1  - Neural Information Processing :25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part I /
AU  - Cheng, Long.
AU  - Leung, Andrew Chi Sing.
AU  - Ozawa, Seiichi.
VL  - 11301
CN  - Q337.5
CN  - TK7882.P3
ID  - 857592
KW  - Optical pattern recognition.
KW  - Artificial intelligence.
KW  - Data mining.
KW  - Computer vision.
KW  - Software engineering.
KW  - Computer science.
SN  - 9783030041670
SN  - 3030041670
TI  - Neural Information Processing :25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part I /
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-04167-0
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-04167-0
ER  -