Hierarchical neural network architectures for vision system

Jin Kun Lin, Gee Gwo Mei, Wentai Liu, Su shing Chen

研究成果: Conference article同行評審

摘要

Using hierarchical neural network architectures (HNN), the authors study the implementations of several vision tasks, including contour finding, motion detection, and line detection (Hough transform). Several models are used. They are homogeneous and heterogeneous Boltzmann machines, homogeneous and heterogeneous Hopfield models, homogeneous winner-take-all model, and the models with and without limited displacement. Simulations have shown that the homogeneous system is capable of handling the desired vision tasks and thus simplifies the implementation.

原文English
頁(從 - 到)511
頁數1
期刊Neural Networks
1
發行號1 SUPPL
DOIs
出版狀態Published - 1988
事件International Neural Network Society 1988 First Annual Meeting - Boston, MA, USA
持續時間: 1988 9月 61988 9月 10

All Science Journal Classification (ASJC) codes

  • 認知神經科學
  • 人工智慧

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