ISSN 2394-5125
 

Research Article 


DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS

SAMMY V. MILITANTE, BOBBY D. GERARDO.

Abstract
Sugarcane diseases are a major threat in the sugarcane industry which leads to the vast destruction of disease-ridden crops, decreases farming, and
large financial loss on small-scale farmers. The loss and farming disaster can be prevented if the early detection of such diseases can be detected and
applying new technologies such as machine learning technology is implemented. Subsequently, deep learning is a current technology in machine
learning that delivers a process to manage with these dilemmas. The research manuscript intends to integrate and train various models of CNN
architecture using a sugarcane image dataset containing 20,000 of disease infected and non-infected sugarcane leaves. There are five trained models
used in the study, these are StridedNet, AlexNet, LeNet, VGGNet, and GoogleNet. The VGGNet model achieves the highest accuracy rate of 95% and
GoogleNet achieves the lowest rate of 65% among the trained models. The trained CNN models are capable in detecting and class ifying sugarcane
leaf images to disease infected and non-infected class based on the outlines of the leaves. Early detection of sugarcane diseases through deep
learning models could help farmers sustain their production and income.

Key words: Sugarcane leaf disease detection; Deep learning; StridedNet; AlexNet; LeNet; VGGNet; GoogleNet


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by SAMMY V. MILITANTE
Articles by BOBBY D. GERARDO
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

SAMMY V. MILITANTE, BOBBY D. GERARDO. DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS. JCR. 2020; 7(15): 620-624. doi:10.31838/jcr.07.15.94


Web Style

SAMMY V. MILITANTE, BOBBY D. GERARDO. DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS. http://www.jcreview.com/?mno=119828 [Access: September 16, 2020]. doi:10.31838/jcr.07.15.94


AMA (American Medical Association) Style

SAMMY V. MILITANTE, BOBBY D. GERARDO. DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS. JCR. 2020; 7(15): 620-624. doi:10.31838/jcr.07.15.94



Vancouver/ICMJE Style

SAMMY V. MILITANTE, BOBBY D. GERARDO. DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS. JCR. (2020), [cited September 16, 2020]; 7(15): 620-624. doi:10.31838/jcr.07.15.94



Harvard Style

SAMMY V. MILITANTE, BOBBY D. GERARDO (2020) DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS. JCR, 7 (15), 620-624. doi:10.31838/jcr.07.15.94



Turabian Style

SAMMY V. MILITANTE, BOBBY D. GERARDO. 2020. DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS. Journal of Critical Reviews, 7 (15), 620-624. doi:10.31838/jcr.07.15.94



Chicago Style

SAMMY V. MILITANTE, BOBBY D. GERARDO. "DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS." Journal of Critical Reviews 7 (2020), 620-624. doi:10.31838/jcr.07.15.94



MLA (The Modern Language Association) Style

SAMMY V. MILITANTE, BOBBY D. GERARDO. "DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS." Journal of Critical Reviews 7.15 (2020), 620-624. Print. doi:10.31838/jcr.07.15.94



APA (American Psychological Association) Style

SAMMY V. MILITANTE, BOBBY D. GERARDO (2020) DETECTING SUGARCANE DISEASES THROUGH ADAPTIVE DEEP LEARNING MODELS. Journal of Critical Reviews, 7 (15), 620-624. doi:10.31838/jcr.07.15.94