Steel Plate Defect Recognition of Deep Neural Network Recognition Based on Space-Time Constraints
In order to improve the effect of real-time defect recognition in steel plate online production, this paper studies the method of steel plate defect recognition based on the deep neural network algorithm based on space-time constraints. Moreover, this paper improves the space-time constraint algorit...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Advances in Multimedia |
| Online Access: | http://dx.doi.org/10.1155/2022/9595286 |
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| Summary: | In order to improve the effect of real-time defect recognition in steel plate online production, this paper studies the method of steel plate defect recognition based on the deep neural network algorithm based on space-time constraints. Moreover, this paper improves the space-time constraint algorithm, optimizes the encryption structure of the traditional ABE scheme, and obtains a neural network feature recognition method based on space-time constraints. In order to process the massive image data stream generated instantaneously and ensure the real-time performance, accuracy, and stability of the detection system, this paper constructs a distributed parallel computing system structure based on the client/server (CC/S) model to obtain an intelligent recognition system. Through experimental research, it can be seen that the deep neural network recognition system based on space-time constraints proposed in this paper has a good effect in the recognition of steel plate defects. |
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| ISSN: | 1687-5699 |