Peanut leaf disease identification with deep learning algorithms.

ABSTRACT: Peanut is an essential food and oilseed crop. One of the most critical factors contributing to the low yield and destruction of peanut plant growth is leaf disease attack, which will directly reduce the yield and quality of peanut plants. The existing works have shortcomings such as strong subjectivity and insufficient generalization ability. So, we proposed a new deep learning model for peanut leaf disease identification. The proposed model is a combination of an improved X-ception, a parts-activated feature fusion module, and two attention-augmented branches. We obtained an accuracy of 99.69%, which was 9.67%-23.34% higher than those of Inception-V4, ResNet 34, and MobileNet-V3. Besides, supplementary experiments were performed to confirm the generality of the proposed model. The propose

SUBMITTER: Xu L 

PROVIDER: S-EPMC10248705 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature