Apple Leaf Disease

Apple leaf disease detection is crucial for optimizing apple production and ensuring food safety, driving research into automated diagnostic systems. Current efforts leverage deep learning, particularly convolutional neural networks (CNNs) like EfficientNet, MobileNet, DenseNet, InceptionResNet, and Xception, often employing transfer learning and ensemble methods to improve classification accuracy of various diseases from images. These models address challenges like image complexity and class imbalance, aiming for high-accuracy identification to enable timely intervention and reduce crop losses. The resulting improved diagnostic tools have significant potential to enhance agricultural practices and minimize economic and health risks associated with apple diseases.

Papers

October 29, 2024

The PV-ALE Dataset: Enhancing Apple Leaf Disease Classification Through Transfer Learning with Convolutional Neural Networks
Joseph Damilola Akinyemi, Kolawole John Adebayo
Convolutional Neural Network Transfer Learning Plant Disease Food Security Apple Leaf Disease

April 10, 2023

An Efficient Transfer Learning-based Approach for Apple Leaf Disease Classification
Md. Hamjajul Ashmafee, Tasnim Ahmed, Sabbir Ahmed, Md. Bakhtiar Hasan, Mst Nura Jahan, A. B. M. Ashikur Rahman
Transfer Learning Deep Learning Based Learning Based Approach Plant Disease Efficient Transfer Apple Leaf Disease

November 25, 2022

MCFFA-Net: Multi-Contextual Feature Fusion and Attention Guided Network for Apple Foliar Disease Classification
Md. Rayhan Ahmed, Adnan Ferdous Ashrafi, Raihan Uddin Ahmed, Tanveer Ahmed
Deep Learning Receptive Field Feature Fusion Attention Guided Network Excitation Network Apple Leaf Disease

October 1, 2022

An Ensemble of Convolutional Neural Networks to Detect Foliar Diseases in Apple Plants
Kush Vora, Dishant Padalia
Convolutional Neural Network Diverse Ensemble Plant Disease Apple Tree Apple Leaf Disease

Apple Leaf Disease

Papers

The PV-ALE Dataset: Enhancing Apple Leaf Disease Classification Through Transfer Learning with Convolutional Neural Networks

An Efficient Transfer Learning-based Approach for Apple Leaf Disease Classification

MCFFA-Net: Multi-Contextual Feature Fusion and Attention Guided Network for Apple Foliar Disease Classification

An Ensemble of Convolutional Neural Networks to Detect Foliar Diseases in Apple Plants