JutePest-YOLO: A Deep Learning Network for Jute Pest Identification and Detection
Author:
Affiliation:
1. School of Mathematics and Computer, Wuhan Polytechnic University, Wuhan, China
2. School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, China
Funder
Key Project of the Scientific Research Program of the Hubei Provincial Department of Education
Major Technical Innovation Projects of Hubei Province
Hubei Provincial Key Laboratory of Intelligent Robot
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10535191.pdf?arnumber=10535191
Reference34 articles.
1. Jute: A Potential Candidate for Phytoremediation of Metals—A Review
2. Effect of Field Duration on Yield and Yield Attributes of Tossa Jute Varieties at Different Agroecological Zones
3. Jute and Jute Products of Bangladesh: Contributions and Challenges
4. Exploring the Future Potential of Jute in Bangladesh
5. Characterization and field evaluation of Spilosoma obliqua nucleopolyhedrosis virus (SpobNPV) CRIJAF1 strain against jute hairy caterpillar, Spilosoma obliqua (Walker) infesting jute, Corchorus olitorius Linn.
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