Lychee Tree Disease Classification and Prediction using Transfer Learning
Author:
Affiliation:
1. Daffodil International University,Department of Computer Science and Engineering,Dhaka,Bangladesh,1341
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9984157/9984211/09984286.pdf?arnumber=9984286
Reference22 articles.
1. YOLOv3-Litchi Detection Method of Densely Distributed Litchi in Large Vision Scenes
2. Deep Learning-Based Instance Segmentation Method of Litchi Canopy from UAV-Acquired Images
3. Modeling for the Prediction of Soil Moisture in Litchi Orchard with Deep Long Short-Term Memory
4. A visual detection method for nighttime litchi fruits and fruiting stems
5. Prevalence of some threatening pests and disease of litchi (Litchi chinensis Sonn.) in Bihar state of India
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1. Real-Time Lightweight Detection of Lychee Diseases with Enhanced YOLOv7 and Edge Computing;Agronomy;2023-11-22
2. Morphological and pathological characterization ofColletotrichumspecies causing anthracnose of litchi leaves in Guangxi, China;Journal of Phytopathology;2023-09-13
3. An Effective Detection of Litchi Disease using Deep Learning;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06
4. Monkeypox Detection from Various Types of Poxes: A Deep Learning Approach;2023 IEEE 8th International Conference for Convergence in Technology (I2CT);2023-04-07
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