An Efficient Disease Detection Technique of Rice Leaf Using AlexNet
Md. Mafiul Hasan Matin, Amina Khatun, Md. Golam Moazzam, Mohammad Shorif Uddin
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.
Topics & Concepts
BlightRice plantSmutComputer scienceLeaf spotArtificial intelligenceHorticultureBiologySmart Agriculture and AISpectroscopy and Chemometric AnalysesPlant Virus Research Studies