Paper
19 August 1998 Hybrid neural networks for gray image recognition
Xujun Ye, Zhineng Li
Author Affiliations +
Abstract
In this paper, a new hybrid neural networks model for gray- level image recognition is presented. By the image segmentation based on the vector quantization which is carried out by Kohonen's self-organizing feature map neural networks, the gray-level image can be mapped into an Hopfield network, each neuron has several states. The performance of this model is compared with that of the traditional model. It is concluded that the new one not only has a smaller number of neurons and interconnections, but also has better error correction capabilities.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xujun Ye and Zhineng Li "Hybrid neural networks for gray image recognition", Proc. SPIE 3561, Electronic Imaging and Multimedia Systems II, (19 August 1998); https://doi.org/10.1117/12.319756
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Cited by 1 scholarly publication.
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KEYWORDS
Neurons

Neural networks

Image processing

Detection and tracking algorithms

Brain mapping

Image segmentation

Performance modeling

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