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rice-leaf-diseases

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A Deep Learning project using Transfer Learning (EfficientNet) and Data Augmentation to classify three major rice leaf diseases (Bacterial Blight, Brown Spot, Leaf Smut). Provides a robust, high-accuracy model for early disease detection in precision agriculture.

  • Updated Feb 28, 2026
  • Jupyter Notebook

A deep learning project for detecting and classifying rice leaf diseases using the ResNet-50 architecture. Includes data augmentation, transfer learning, and evaluation metrics such as accuracy, precision, recall, and confusion matrix. Achieves over 98% accuracy in classifying four classes: Bacterial Blight, Blast, Brown Spot, and Tungro.

  • Updated Dec 14, 2024
  • Jupyter Notebook

This project aims to detect diseases on the leaves of rice plants in Indonesia using the Convolutional Neural Network (CNN) Inception V3 method to design a classification model and produce a high level of accuracy.

  • Updated Oct 12, 2023
  • Jupyter Notebook

A complete mobile image classification app built with Lambda Native framework, featuring knowledge distillation and GPU-accelerated training. The app can classify images into 5 custom categories with real-time inference on mobile devices.

  • Updated Oct 28, 2025
  • Python

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