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10 November 2022 Attention-based feature enhancement for rice leaf disease recognition
Hengshun Zhang
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Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 1234806 (2022) https://doi.org/10.1117/12.2641832
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China
Abstract
Automatic recognition of rice leaf diseases has always been a research hotspot in the smart agriculture community, which can provide key information for pest control and scientific production decision-making. Benefiting from the rapid development of the convolutional neural networks, the accuracy has made a breakthrough, while still limited when the lesion area is quite small in the early stage. To this end, in this paper, we propose an attention-based feature enhancement strategy for rice leaf diseases recognition. specially, we first capture the discriminative features through learning several independent spatial attention maps, which are highly responsive to categories. We further fuse these local discriminative features based on the contribution scores of different features to the category. With extensive experiments on benchmark data set RiceLeafs, we achieve a training accuracy of 99.68% and a testing accuracy of 87.60%, which verifies the effectiveness of our method.
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Hengshun Zhang "Attention-based feature enhancement for rice leaf disease recognition", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 1234806 (10 November 2022); https://doi.org/10.1117/12.2641832
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KEYWORDS
Feature extraction
Visualization
Agriculture
Detection and tracking algorithms
Image segmentation
Data modeling
Image classification
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