Paper
28 March 2023 Research on tomato leaf disease identification based on deep learning
Kunao Zhang, Zhenxing Liang
Author Affiliations +
Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125664L (2023) https://doi.org/10.1117/12.2667384
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China
Abstract
Tomato is one of the important economic forest fruits in my country. It is the fourth largest vegetable and fruit in my country with an annual output of about 55 million tons, accounting for 7% of the total vegetables. Due to the wide planting area, large yield, and high-quality vegetables are the development direction of modern agriculture. Therefore, this paper adopts the deep learning method, uses the CNN to collect the leaves of tomato diseases and pest detection, uses the stacking to detect the diseases and insect pests on the leaves with the optimized DenseNet121 and MobileNet-V2, and compares the individual DenseNet121 model and MobileNet-V2 model. It shows that the detection results of pests and diseases after fusion are higher than other algorithms, and the final detection accuracy reaches 98.24%, which effectively improves the detection accuracy. It provides a more effective method for the treatment of tomato diseases and insect pests.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kunao Zhang and Zhenxing Liang "Research on tomato leaf disease identification based on deep learning", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125664L (28 March 2023); https://doi.org/10.1117/12.2667384
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Convolution

Data modeling

Image processing

Technology

Agriculture

Deep learning

Performance modeling

RELATED CONTENT


Back to Top