Synergizing Insights for Precise Rice Leaf Disease Diagnosis Via Multi-Modal Fusion
- Title
- Synergizing Insights for Precise Rice Leaf Disease Diagnosis Via Multi-Modal Fusion
- Creator
- Pally S.C.; Jenefa J.
- Description
- Rice holds a significant position in India, especially in the southern part of the country, where people tend to eat some rice at least once a day. Farmers are facing a huge loss due to diseases in leaf, which is the main problem of agriculture. By using techniques like machine learning, main problems detection can be done. This review, discusses common plant diseases that affect the leaf. Some include Leaf Spots, Rusts, Fusarium Wilt, Early Blight, Powdery Mildew and Downey Mildew. Our research found that machine learning techniques on rice plants make finding diseases on leaves easier. Finally, we concluded that the most accurate method is the Enhanced VGG16, with an accuracy of 99.60% because it is really good at spotting diseases on rice leaves because it's great at recognizing the small details and patterns in leaf pictures. This helps it to tell the diseases apart more accurately and make fewer mistakes in identifying them. 2024 IEEE.
- Source
- 10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024, pp. 1602-1607.
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Early Blight of rice; Fusarium Wilt of rice; Leaf Spots of rice; Powdery Mildew of rice and Downey Mildew of rice; Rusts of rice
- Coverage
- Pally S.C., Christ (Deemed to be University), Dept. of Computer Science and Engineering, Karnataka, Bengaluru, India; Jenefa J., Christ (Deemed to be University), Dept. of Computer Science and Engineering, Karnataka, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835038436-9
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Pally S.C.; Jenefa J., “Synergizing Insights for Precise Rice Leaf Disease Diagnosis Via Multi-Modal Fusion,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19102.