Classifying Crop Leaf Diseases using Different Deep Learning Models with Transfer Learning

2024/07/01 by Lakshin Pathak, Mili Virani, Drashti Kansara · 1 citation
Agricultural and Biological Sciences · #Greenhouse Technology and Climate Control #Leaf Properties and Growth Measurement #Smart Agriculture and AI

paper · pdf · doi:10.38124/ijisrt/ijisrt24jun654

openalex publication_date 2024/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Within the scope of the research, we put forward a technique of exactly confirming the distinctiveness of agricultural leaf pathologies with the assist of deep mastering algorithms and switch getting to know generation. We have pre-skilled models like VGG19, MobileNet, InceptionV3, EfficientNetB0, Simple CNN where we are seeking to increase the utility for the crop disorder type. Through searching at some metrics as cited Accuracy, Precision, Recall and F1 score for a better knowledge of a crop leaf photo category, we observe how each version performs. Our paper shows that artificial intelligence is fairly useful for the obligations of the automatic disease detection and switch mastering (as a method for reusing the existing understanding in the new software) is also beneficial. The contribution of this work to the development of reliable systems of save you sicknesses in production touches upon the rural exercise to achieve superiority fits into precision agriculture and sustainable farming. Future research ought to possibly include centered regions concerning a stability of datasets and stepped forward model interpretability which in turn will improve the fulfillment of these strategies in agricultural contexts.

Citations

• Factors Associated with Membership in a Mutual Health Insurance Fund in the Thiès Region (Senegal) in 2023: Article
• Loss of Life Transformer Prediction Based on Stacking Ensemble Improved by Genetic Algorithm By IJISRT
• Beyond Mobile Payments: Exploring the Evolution and Future of Fintech (BY IJISRT)
• Fault Detection Method based on Artificial Neural Network for 330kV Nigerian Transmission Line
• Enhancements in Immediate Speech Emotion Detection: Harnessing Prosodic and Spectral Characteristics
• E-Commerce Promotional Products Selection Using SWARA and TOPSIS
• Knowledge of Intestinal Parasitic Infection and Anemia among Pregnant Women Attending Antenatal Clinic in Ogun State
• Analysis of Work Measurement Using a Stopwatch in a Motorcycle Workshop
• Ethnobotanical Studies of Reputed Aphrodisiac Plants Used in Traditional Medicine in Haut-Katanga in DR of Congo
• Analysis of Selected Physical Fitness, Physiological, and Psychological Variables among Government, Government-Aided, and Private School Boys in Chennai District
• Implementation of Total Productive Maintenance on Frame Welding Machine Maintenance Using the Overall Equipment Effectiveness (OEE) Method at PT Electronics Components Indonesia

Cited by

• Haematological Studies of Broilers (1-28 Days) Fed with Diet Containing Varying Proportions of Tithonia Diversifolia Leaf Protein Concentrate

Related

• Comparative Analysis of Deep Learning Models for Crop Disease Detection: A Transfer Learning Approach
• Explainable AI-Enhanced Deep Learning for Pumpkin Leaf Disease Detection: A Comparative Analysis of CNN Architectures
• Leaf diseases detection using deep learning methods
• An Approach Towards Identifying Bangladeshi Leaf Diseases through Transfer Learning and XAI
• PLDC‐Net: A Domain‐Specific Base Model for Plant Leaf Disease Classification Domain Adaptation Tasks