Automated Black Rust Detection in Wheat Using CNNs: Advanced CNN-Based Approach for Early Detection and Management of Black Rust in Wheat - Softcover

Roy, Rupsha; Mondal, Saptarshi

 
9786207843930: Automated Black Rust Detection in Wheat Using CNNs: Advanced CNN-Based Approach for Early Detection and Management of Black Rust in Wheat
Softcover
ISBN 10: 6207843932 ISBN 13: 9786207843930
Verlag: LAP LAMBERT Academic Publishing, 2025

Inhaltsangabe

This research introduces a highly accurate CNN-based model (99.9% accuracy) for early detection of black rust in wheat using image analysis. The model was trained on a diverse, region-specific dataset, ensuring robust performance across varying agro-climatic conditions. It enables early-stage disease detection, reducing yield loss, optimizing fungicide use, and promoting sustainable farming practices. The system is lightweight, deployable on smartphones, and integrates with digital farming ecosystems, empowering farmers with accessible AI tools. Its scalability and compatibility with IoT and cloud platforms position it as a vital step toward precision agriculture and national food security.

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Über die Autorin bzw. den Autor

Rupsha Roy, B.Sc (Hons) Agriculture 3rd year student at Adamas University, focuses on climate-resilient farming. Saptarshi Mondal, B.Tech CSE (AIML) 3rd year student at Adamas University, has published a Springer paper on AI for disabled assistance. Both collaborate Automated Black Rust Detection in Wheat using CNNs.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2025
Sprache
Englisch
ISBN 10 
6207843932
ISBN 13 
9786207843930
Einband
Taschenbuch
Anzahl der Seiten
56
Kontakt zum Hersteller
preigu GmbH & Co. KG
mail@preigu.de

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