Reinforcement Learning-Driven Active Few-Shot Learning Framework with Hyperparameter Optimization for Rice Pest Classification
Author:
Affiliation:
1. Technological Institute of the Philippines, Philippines
2. Northern Iloilo State University, Philippines
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3676581.3676591
Reference41 articles.
1. United States Department of Agriculture. 2023. World Agricultural Supply and Demand Estimates. https://usda.library.cornell.edu/concern/publications/3t945q76s?locale=en
2. DA Press Office. 2022. FROM BUSINESS MIRROR: Philippine Rice Production Varieties and Research: What We Know So Far. https://www.da.gov.ph/from-business-mirror-philippine-rice-production-varieties-and-research-what-we-know-so-far/
3. BPI. 2020. Philippine Pest Surveillance and Early Warning Protocol for Rice. Bureau of Plant Industry, Malate Manila 51p.
4. Jean-Philippe Deguine Jean-Noël Aubertot Rica Joy Flor Françoise Lescourret Kris A G Wyckhuys and Alain Ratnadass. Integrated pest management: good intentions hard realities. A review. https://doi.org/10.1007/s13593-021-00689-w/Published
5. Automatic Detection and Monitoring of Insect Pests—A Review
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