ISSN 2394-5125
 

Research Article 


DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW

Subodh Bansal, Anuj Kumar.

Abstract
Image-based maize disease detection is essential to protect the crop by early detection of the diseases, and to
increase its yield. Deep learning based detection systems has gained the attention of many researchers in recent times,
especially with the increase in the computational power of modern Graphics Processing Units. The present study presents a
comprehensive review of the deep learning frameworks for maize disease detection. The study highlighted the findings from
the survey and specified its future scope. Additionally, a detailed taxonomy of important maize diseases, along with their
visual symptoms in the early and later stages is presented. These symptoms are useful for classification of diseases in imagebased
techniques. The steps involved in a deep learning system for image classification are described, along with their pros
and cons. The article will allow the reader to gain valuable insights, along with the path to follow for progress in the
concerned field.

Key words: Deep Learning, Maize Disease Detection, Convolution Neural Networks, Image Classification


 
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Pubmed Style

Subodh Bansal, Anuj Kumar. DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW. JCR. 2020; 7(9): 43-49. doi:10.31838/jcr.07.09.8


Web Style

Subodh Bansal, Anuj Kumar. DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW. http://www.jcreview.com/?mno=112905 [Access: May 30, 2021]. doi:10.31838/jcr.07.09.8


AMA (American Medical Association) Style

Subodh Bansal, Anuj Kumar. DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW. JCR. 2020; 7(9): 43-49. doi:10.31838/jcr.07.09.8



Vancouver/ICMJE Style

Subodh Bansal, Anuj Kumar. DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW. JCR. (2020), [cited May 30, 2021]; 7(9): 43-49. doi:10.31838/jcr.07.09.8



Harvard Style

Subodh Bansal, Anuj Kumar (2020) DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW. JCR, 7 (9), 43-49. doi:10.31838/jcr.07.09.8



Turabian Style

Subodh Bansal, Anuj Kumar. 2020. DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW. Journal of Critical Reviews, 7 (9), 43-49. doi:10.31838/jcr.07.09.8



Chicago Style

Subodh Bansal, Anuj Kumar. "DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW." Journal of Critical Reviews 7 (2020), 43-49. doi:10.31838/jcr.07.09.8



MLA (The Modern Language Association) Style

Subodh Bansal, Anuj Kumar. "DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW." Journal of Critical Reviews 7.9 (2020), 43-49. Print. doi:10.31838/jcr.07.09.8



APA (American Psychological Association) Style

Subodh Bansal, Anuj Kumar (2020) DEEP LEARNING FRAMEWORKS FOR MAIZE DISEASE DETECTION: A REVIEW. Journal of Critical Reviews, 7 (9), 43-49. doi:10.31838/jcr.07.09.8