ArticleComputational intelligence and neuroscience2022
Improved AlexNet with Inception-V4 for Plant Disease Diagnosis.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- A lightweight co-optimization model for field sunflower disease identification.Frontiers in plant science · 2025Article
- A segmentation model to detect cevical lesions based on machine learning of colposcopic images.Heliyon · 2023Article
- Classification ofPlants (Basel, Switzerland) · 2023Article
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8 authors.
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Abstract
Timely disease detection and pest treatment are key issues in modern agricultural production, especially in large-scale crop agriculture. However, it is very time and effort-consuming to identify plant diseases manually. This paper proposes a deep learning model for agricultural crop disease identification based on AlexNet and Inception-V4. AlexNet and Inception-V4 are combined and modified to achieve an efficient but good performance. Experimental results on the expanded PlantVillage dataset show that the proposed model outperforms the compared methods: AlexNet, VGG11, Zenit, and VGG16, in terms of accuracy and
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