Segmenting Crop Disease Leaf Image by Modified Fully-Convolutional Networks

Crop disease leaf image segmentation is an important and challenging step, because the disease leaf image and corresponding lesions are often complex, various, and variant, and the segmenting results directly impact on subsequent disease recognition rate. A segmentation algorithm is proposed by modified fully convolutional networks (FCNs) to deal with the problem of segmenting spots from crop leaf disease image with complicated background. The experimental result shows that the proposed method can be used in complicated field environment with high extracting accuracy.

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