Using Local Invariant in Occluded Object Recognition by Hopfield Neural Network
碩士 === 國立中山大學 === 機械與機電工程學系研究所 === 91 === In our research, we proposed a novel invariant in 2-D image contour recognition based on Hopfield-Tank neural network. At first, we searched the feature points, the position of feature points where are included high curvature and corner on the contour. We us...
Main Authors: | Chih-Hung Tzeng, 曾智宏 |
---|---|
Other Authors: | Innchyn Her |
Format: | Others |
Language: | zh-TW |
Published: |
2003
|
Online Access: | http://ndltd.ncl.edu.tw/handle/61679627653397484929 |
Similar Items
-
Learning View Invariant Recognition with Partially Occluded Objects
by: James Matthew Tromans, et al.
Published: (2012-07-01) -
Using a Spatiotemporal Neural Network for the Recognition of Partially Occluded Objects
by: Chia-Pin Wu, et al.
Published: (1995) -
Improving the local minima of the Hopfield network for optimization and its application to object recognition
by: Peng, Mengkang
Published: (1995) -
Chinese Sign Language Recognition Using Hopfield Neural Network
by: Huang, Wen Yi, et al.
Published: (1995) -
Image Recognition using Hopfield Neural Network combine Gaussian Filter
by: Lu, Chunhua, et al.
Published: (2011)