Effect of Learning Rate on the Recognition of Images
This paper presents a study for the effect of learning rate on an approach for texture classification and detection based on the neural network principle. This neural network consists of three layers, which are input, output, and hidden layers. The back propagation technique is considered. A compute...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
1996-01-01
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| Series: | Active and Passive Electronic Components |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1155/1996/45086 |
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| Summary: | This paper presents a study for the effect of learning rate on an approach for texture classification and
detection based on the neural network principle. This neural network consists of three layers, which are
input, output, and hidden layers. The back propagation technique is considered. A computer algorithm
is deduced and applied. In this work, the synthetic textures are generated. The results are taken for the
modern computer of AT 486 type. The mathematical analysis is summarized in order to illustrate the
effect of learning rate parameter on the exact discrimination during processing. This effect is studied
through applications. The minimum consumed time for the computational time of classification in
industry is correlated to correspond only the use of only 2 units in the hidden layer of a neural network
for real images instead of 11 units. |
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| ISSN: | 0882-7516 1563-5031 |