Increment Learning and Rapid Retrieval of Visual Information Based on Pattern Association Memory-Reference-Cited by-同舟云学术

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Increment Learning and Rapid Retrieval of Visual Information Based on Pattern Association Memory

Published:2018-01-27 Issue:3 Volume:48 Page:1597-1610
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Deng Limiao^ORCID,Gao Mingyue,Wang Yanjiang

Funder

Natural Science Foundation of Shandong Provence

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

http://link.springer.com/article/10.1007/s11063-018-9789-5/fulltext.html

Reference41 articles.

1. Fei-Fei L, Perona P (2005) A bayesian hierarchical model for learning natural scene categories. In: IEEE computer society conference on computer vision and pattern recognition, vol 2. IEEE, pp 524–531

2. Cisek P, Drew T, Kalaska J (2007) Computational neuroscience: theoretical insights into brain function. Elsevier, Amsterdam

3. Tao D, Li X, Wu X, Maybank SJ (2009) Geometric mean for subspace selection. IEEE Trans Pattern Anal Mach Intell 31(2):260–274

4. Albus JS (2010) A model of computation and representation in the brain. Inf Sci 180(9):1519–1554

5. Kirkpatrick J, Pascanu R, Rabinowitz N, Veness J, Desjardins G, Rusu AA et al (2017) Overcoming catastrophic forgetting in neural networks. Proc Natl Acad Sci USA 114(13):3521–3526

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1. Visual Images Memory Recall Based on ClassRBM and Free Energy Minimization;2020 15th IEEE International Conference on Signal Processing (ICSP);2020-12-06

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