A multi-type crop leaf disease identification method based on a dynamic neural network
A dynamic neural network and identification method technology, applied in the field of plant disease detection, can solve problems such as the inability to better identify various crop leaf diseases, and achieve the effects of meeting real-time requirements, improving accuracy, and reducing consumption of computing resources.
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[0064] In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can also be implemented in other ways than those described here. Therefore, the present invention is not limited to the specific embodiments disclosed below.
[0065] The invention uses a segmented convolutional network to eliminate the background of leaf disease images and extract effective information, and uses a dynamic convolution module to adaptively adjust the convolution kernel according to the severity of plant leaf diseases to extract disease features, and then introduces The shallow classifier and the early exit mechanism dynamically adjust the network structure, realizing the au...
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