Deep Learning Architectures for Fruit and Leaf Disease Detection: A Critical Analysis of Methods, Metrics, Challenges, and Future Research Directions

Deep Learning Techniques for Citrus Disease Detection: A Comprehensive Review

Citrus crops are economically vital worldwide, yet they remain highly susceptible to a range of infectious diseases that cause considerable yield and quality losses each year. Early and accurate disease identification is fundamental to sustainable orchard management and food security. Over the past decade, deep learnin...

A Comprehensive Survey on Machine Learning and Deep Learning Approaches for Potato Leaf Disease Detection

A comprehensive and systematic review of state-of-the-art methods for detecting potato leaf disease, covering convolutional neural networks, transformer-based architectures, and hybrid models, and a strategic comparative analysis is conducted.

Deep Learning-based Bean Leaf Disease Classification: A Comparison of ResNet50 and VGG19

This work demonstrates ResNet50’s performance for bean leaf disease classification tasks, providing important insights for future research and practical applications in agricultural disease control.

A Comparative Study of Deep Learning-Based Pest Detection Models with Interpretability and Deployment Strategies for Medicinal Plants

A comparative analysis of five deep learning models, namely Basic CNN, VGG16, ResNet50, VGG32, and the proposed CFNET, which is based on EfficientNetB3, for binary pest detection in medicinal plants confirms CFNET's suitability for mobile and edge-based agricultural monitoring systems.

A comparative study of deep learning models for tomato disease detection

Deep Learning Approaches for Apple Disease Classification and Detection: A PRISMA 2020 Systematic Literature Review

This systematic literature review integrates 30 peer-reviewed studies published between 2020 and 2026, selected from 180 database records using a PRISMA 2020-aligned protocol to highlight standardized real-orchard benchmarks, cross-dataset validation, calibrated and explainable predictions, reproducible experimental pr...