Rice Leaf Disease Detection and Classification Using Shallow Trained Yolov7 Active Deep Learning Approach
Author:
Affiliation:
1. Charles Sturt University,School of Computing, Mathematics and Engineering,Bathurst,NSW,Australia,2795
2. Feni University,Department of EEE,Feni,Bangladesh,5660
3. Daegu Catholic University,Department of Semiconductor Electronic Engineering,Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10410651/10410903/10410911.pdf?arnumber=10410911
Reference21 articles.
1. Bangladesh: Grain and Feed Update. USDA Foreign Agricultural Service,2021
2. Diseases-IRRI Rice Knowledge Bank,2021
3. Bacterial blight-IRRI Rice Knowledge Bank,2021
4. Research on Multi-Scale Pest Detection and Identification Method in Granary Based on Improved YOLOv5, Agriculture;Chu,2023
5. TIA-YOLOv5: An improved YOLOv5 network for real-time detection of crop and weed in the field
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