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Attention Selection with Self-supervised Competition Neural Network and Its Applications in Robot

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Advances in Neural Networks – ISNN 2007 (ISNN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4491))

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Abstract

This paper proposes a novel attention selection system with competition neural network supervised by visual memory. As compared with others, this system can not only attend some salient regions randomly according to sensory information but also mainly focus on some learned objects by the visual memory. So it can be applied in robot self-localization or object tracking. The weights of neural networks can be adapted in real time to environment change.

No.60571052, 30370392 supported by NSF; No.045115020 supported by Shanghai Science and Technology Committee.

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Author information

Authors and Affiliations

  1. Electronic Engineering Department, Fudan University Shanghai, 200433, China

    Chenlei Guo & Liming Zhang

Authors
  1. Chenlei Guo
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  2. Liming Zhang
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering (M/C 154), University of Illinois at Chicago, 851 S. Morgan Street, 60607-7053, Chicago, IL, USA

    Derong Liu

  2. School of Automation, Southeast University, 210096, Nanjing, China

    Shumin Fei

  3. Laboratory of Complex Systems, Institute of Automation, Chinese Adacemy of Sciences, 100080, Beijing, P. R. China

    Zeng-Guang Hou

  4. School of Information Science and Engineering, Northeast University, Shenyang, 110004, China

    Huaguang Zhang

  5. School of Electrical Engineering, Hohai University, Nanjing, 210098, China

    Changyin Sun

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© 2007 Springer-Verlag Berlin Heidelberg

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Guo, C., Zhang, L. (2007). Attention Selection with Self-supervised Competition Neural Network and Its Applications in Robot. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_85

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  • DOI: https://doi.org/10.1007/978-3-540-72383-7_85

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72382-0

  • Online ISBN: 978-3-540-72383-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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