← All publicationsITIS 2025🏆 Best Paper AwardPublished
A Comparative Study of Deep Learning Approaches for Apple Leaf Disease Classification
Comparative analysis of deep learning architectures (InceptionV3, ResNet50, EfficientNetB0, MobileNetV2) for apple leaf disease classification across multiple public datasets, achieving a peak testing accuracy of 98.89%.
Results
Test accuracy: 98.89%
Compared models: InceptionV3, ResNet50, EfficientNetB0, MobileNetV2
🏆 Best Paper Award
Awarded for A Comparative Study of Deep Learning Approaches for Apple Leaf Disease Classification — recognized for exceptional quality, originality, and contribution to research.
ITIS 2025 — IEEE 11th Information Technology International Seminar · October 9, 2025 · Cert # 596/UN63.7/TU/2025
deep learningcomparative studyapple leaf diseaseInceptionV3ResNet50EfficientNetB0MobileNetV2