Rice Leaf Disease

Rice leaf disease detection is crucial for ensuring global food security, as timely identification prevents yield losses and promotes sustainable agriculture. Current research heavily utilizes Convolutional Neural Networks (CNNs), particularly lightweight architectures like MobileNetV2 and EfficientNet, and pre-trained models such as ResNet and Inception, often enhanced by feature extraction techniques like HOG, to achieve high accuracy in classifying various rice diseases from images. These advancements are being translated into user-friendly applications for farmers, enabling real-time disease diagnosis and personalized recommendations. The development of robust and accessible diagnostic tools represents a significant step towards improving rice cultivation practices worldwide.

Papers

September 17, 2024

Analysis of Convolutional Neural Network-based Image Classifications: A Multi-Featured Application for Rice Leaf Disease Prediction and Recommendations for Farmers
Biplov Paneru, Bishwash Paneru, Krishna Bikram Shah
General Analysis Deep Convolutional Neural Network Disease Detection Precision Agriculture Different Convolutional Neural Network Real Time Prediction Small Farmer Rice Leaf Disease Network Classification

August 3, 2024

Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification
Khairun Saddami, Yudha Nurdin, Mutia Zahramita, Muhammad Shahreeza Safiruz
Smart Agriculture Green AI Lightweight CNN Mobile CNN Rice Leaf Disease Rice Disease

February 26, 2024

Leveraging Pre-trained CNNs for Efficient Feature Extraction in Rice Leaf Disease Classification
Md. Shohanur Islam Sobuj, Md. Imran Hossen, Md. Foysal Mahmud, Mahbub Ul Islam Khan
Convolutional Neural Network Feature Extraction Disease Detection Pre Trained Convolutional Neural Network Rice Leaf Disease

September 14, 2023

Dhan-Shomadhan: A Dataset of Rice Leaf Disease Classification for Bangladeshi Local Rice
Md. Fahad Hossain
Data Set Disease Detection Rice Kernel Rice Leaf Disease

January 13, 2023

Development of a Prototype Application for Rice Disease Detection Using Convolutional Neural Networks
Harold Costales, Arpee Callejo-Arruejo, Noel Rafanan
Convolutional Neural Network Development Activity Image Processing Visual Prototype Rice Leaf Disease Rice Disease Detection

September 4, 2022

Rice Leaf Disease Classification and Detection Using YOLOv5
Md Ershadul Haque, Ashikur Rahman, Iftekhar Junaeid, Samiul Ul Hoque, Manoranjan Paul
Data Detection Fire YOLOv5 Attains Rice Kernel Rice Leaf Disease Rice Disease Detection

Rice Leaf Disease

Papers

Analysis of Convolutional Neural Network-based Image Classifications: A Multi-Featured Application for Rice Leaf Disease Prediction and Recommendations for Farmers

Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification

Leveraging Pre-trained CNNs for Efficient Feature Extraction in Rice Leaf Disease Classification

Dhan-Shomadhan: A Dataset of Rice Leaf Disease Classification for Bangladeshi Local Rice

Development of a Prototype Application for Rice Disease Detection Using Convolutional Neural Networks

Rice Leaf Disease Classification and Detection Using YOLOv5