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Author:

Miao, Jun (Miao, Jun.) | Duan, Lijuan (Duan, Lijuan.) (Scholars:段立娟) | Qing, Laiyun (Qing, Laiyun.) | Qiao, Yuanhua (Qiao, Yuanhua.) (Scholars:乔元华)

Indexed by:

EI Scopus

Abstract:

This paper presents an improved neural architecture for gaze movement control in target searching. Compared with the four-layer neural structure proposed in [14], a new movement coding neuron layer is inserted between the third layer and the fourth layer in previous structure for finer gaze motion estimation and control. The disadvantage of the previous structure is that all the large responding neurons in the third layer were involved in gaze motion synthesis by transmitting weighted responses to the movement control neurons in the fourth layer. However, these large responding neurons may produce different groups of movement estimation. To discriminate and group these neurons' movement estimation in terms of grouped connection weights form them to the movement control neurons in the fourth layer is necessary. Adding a new neuron layer between the third layer and the fourth lay is the measure that we solve this problem. Comparing experiments on target locating showed that the new architecture made the significant improvement. © 2011 IEEE.

Keyword:

Network architecture Motion estimation Neural networks Neurons

Author Community:

  • [ 1 ] [Miao, Jun]Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
  • [ 2 ] [Duan, Lijuan]College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Qing, Laiyun]School of Information Science and Engineering, Graduate University, Chinese Academy of Sciences, Beijing 100049, China
  • [ 4 ] [Qiao, Yuanhua]College of Applied Science, Beijing University of Technology, Beijing 100124, China

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Year: 2011

Page: 2341-2348

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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