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Automated Sugarcane Leaf Disease Detection Using AI Models
Angličtina
95 b
Až 30 dní na vrátenie tovaru
This book explores the application of artificial intelligence in agriculture, focusing on automated detection of sugarcane leaf diseases. It presents a comprehensive study comparing classical machine learning models such as Decision Tree, Random Forest, AdaBoost, Gradient Boosting, SVM, and MLP with deep learning Convolutional Neural Networks. Using the Sugarcane Leaf Disease Dataset, the book details image preprocessing, feature extraction, model training, and evaluation with metrics such as accuracy, precision, recall, and F1-score. It highlights the advantages, challenges, and practical deployment potential of AI-driven disease detection in real-world agricultural settings, providing valuable insights for researchers, agronomists, and farmers seeking sustainable crop management solutions.
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