Article

Game Theory-Infused Hybrid CatBoost- Extreme Learning Machine model for Reliable Identification of Rice Leaf Diseases for Advancing Agricultural Surveillance

2024-03-11

Abstract excerpt

The global economy greatly relies on rice cultivation, yet the agricultural sector is primarily challenged by the prevalence of rice leaf diseases. This research introduces a novel Game Theory-Infused Hybrid CatBoost-Extreme Learning Machine (GT-CBELM) model tailored for the accurate and dependable detection of rice leaf diseases, thereby advancing agricultural surveillance practices. The proposed methodology harn...

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Literature Corpus work: c4e5953f-ef3d-5570-aec6-8d56a90195d0
DOI: 10.21203/rs.3.rs-3996107/v1

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Game Theory-Infused Hybrid CatBoost- Extreme Learning Machine model for Reliable Identification of Rice Leaf Diseases for Advancing Agricultural SurveillanceDOI 10.21203/rs.3.rs-3996107/v1Read

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