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Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part II / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 9948
- Theoretical Computer Science and General Issues, 2512-2029 ; 9948
- Language:
- English
- Subjects (All):
- Pattern recognition systems.
- Computer vision.
- Artificial intelligence.
- Computer science.
- Data mining.
- Application software.
- Automated Pattern Recognition.
- Computer Vision.
- Artificial Intelligence.
- Theory of Computation.
- Data Mining and Knowledge Discovery.
- Computer and Information Systems Applications.
- Local Subjects:
- Automated Pattern Recognition.
- Computer Vision.
- Artificial Intelligence.
- Theory of Computation.
- Data Mining and Knowledge Discovery.
- Computer and Information Systems Applications.
- Physical Description:
- 1 online resource (XIX, 739 pages) : 252 illustrations
- Edition:
- 1st ed. 2016.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2016.
- System Details:
- text file PDF
- Summary:
- The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms. .
- Contents:
- Deep and reinforcement learning
- Big data analysis
- Neural data analysis.-Robotics and control
- Bio-inspired/energy efficient information processing.-Whole brain architecture
- Neurodynamics
- Bioinformatics
- Biomedical engineering
- Data mining and cybersecurity workshop
- Machine learning.-Neuromorphic hardware
- Sensory perception
- Pattern recognition
- Social networks
- Brain-machine interface
- Computer vision
- Time series analysis.-Data-driven approach for extracting latent features
- Topological and graph based clustering methods
- Computational intelligence
- Data mining
- Deep neural networks
- Computational and cognitive neurosciences
- Theory and algorithms.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-46672-9
- 9783319466729
- Access Restriction:
- Restricted for use by site license.
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