TITLE:
An Efficient Disease Detection Technique of Rice Leaf Using AlexNet
AUTHORS:
Md. Mafiul Hasan Matin, Amina Khatun, Md. Golam Moazzam, Mohammad Shorif Uddin
KEYWORDS:
AlexNet, Leaf Diseases, Disease Prediction, Rice Leaf Disease Dataset, Disease Classification
JOURNAL NAME:
Journal of Computer and Communications,
Vol.8 No.12,
December
14,
2020
ABSTRACT: As nearly half of the people in the world live on rice, so the rice leaf disease detection is very important for our agricultural sector. Many researchers worked on this problem and they achieved different results according to their applied techniques. In this paper, we applied AlexNet technique to detect the three prevalence rice leaf diseases termed as bacterial blight, brown spot as well as leaf smut and got a remarkable outcome rather than the previous works. AlexNet is a special type of classification technique of deep learning. This paper shows more than 99% accuracy due to adjusting an efficient technique and image augmentation.