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AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM

Plant disease can affect the productivity of either hobbyist or commercial farmers. This in tum can result in loss of the crop and cause financial loss to the fanner8. The current method ofmanuaIIy recognizing a disease requires either the farmers have had experience beforehand in recognizing the ty...

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Bibliographic Details
Main Author: Vera Ruth, Rewcastle
Format: Final Year Project Report
Language:English
English
Published: Universiti Malaysia Sarawak (UNIMAS) 2019
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://ir.unimas.my/id/eprint/34876/1/AUTOMATED%20PLANT%20DISEASE%20DETECTION%20USING%20DEEP%20LEARNING%20ON%20MOBILE%20PLATFORM%20-%2024%20pgs.pdf
http://ir.unimas.my/id/eprint/34876/4/AUTOMATED%20PLANT%20DISEASE%20DETECTION%20USING%20DEEP%20LEARNING%20ON%20MOBILE%20PLATFORM.pdf
http://ir.unimas.my/id/eprint/34876/
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spelling my.unimas.ir.348762024-09-17T07:15:12Z http://ir.unimas.my/id/eprint/34876/ AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM Vera Ruth, Rewcastle QA75 Electronic computers. Computer science Plant disease can affect the productivity of either hobbyist or commercial farmers. This in tum can result in loss of the crop and cause financial loss to the fanner8. The current method ofmanuaIIy recognizing a disease requires either the farmers have had experience beforehand in recognizing the type of disease or with the help of a horticulturist. This would be difficult and costly for farmers to employ a professional horticulturist or rely on knowledge gained through experience. Therefore, this project aims at developing a mobile applicatiJ:;m which is equipped with deep learning algorithm to enable the detection and identification of a disease for a particular plant. This solution provides portable platform, real time result, and without the needs of professional expert to recognize the disease. The infonnation gathered can then be compiled and shared to relevant stakeholders for record purpose, analytics and future references. Universiti Malaysia Sarawak (UNIMAS) 2019 Final Year Project Report NonPeerReviewed text en http://ir.unimas.my/id/eprint/34876/1/AUTOMATED%20PLANT%20DISEASE%20DETECTION%20USING%20DEEP%20LEARNING%20ON%20MOBILE%20PLATFORM%20-%2024%20pgs.pdf text en http://ir.unimas.my/id/eprint/34876/4/AUTOMATED%20PLANT%20DISEASE%20DETECTION%20USING%20DEEP%20LEARNING%20ON%20MOBILE%20PLATFORM.pdf Vera Ruth, Rewcastle (2019) AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM. [Final Year Project Report] (Unpublished)
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Vera Ruth, Rewcastle
AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM
description Plant disease can affect the productivity of either hobbyist or commercial farmers. This in tum can result in loss of the crop and cause financial loss to the fanner8. The current method ofmanuaIIy recognizing a disease requires either the farmers have had experience beforehand in recognizing the type of disease or with the help of a horticulturist. This would be difficult and costly for farmers to employ a professional horticulturist or rely on knowledge gained through experience. Therefore, this project aims at developing a mobile applicatiJ:;m which is equipped with deep learning algorithm to enable the detection and identification of a disease for a particular plant. This solution provides portable platform, real time result, and without the needs of professional expert to recognize the disease. The infonnation gathered can then be compiled and shared to relevant stakeholders for record purpose, analytics and future references.
format Final Year Project Report
author Vera Ruth, Rewcastle
author_facet Vera Ruth, Rewcastle
author_sort Vera Ruth, Rewcastle
title AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM
title_short AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM
title_full AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM
title_fullStr AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM
title_full_unstemmed AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM
title_sort automated plant disease detection using deep learning on mobile platform
publisher Universiti Malaysia Sarawak (UNIMAS)
publishDate 2019
url http://ir.unimas.my/id/eprint/34876/1/AUTOMATED%20PLANT%20DISEASE%20DETECTION%20USING%20DEEP%20LEARNING%20ON%20MOBILE%20PLATFORM%20-%2024%20pgs.pdf
http://ir.unimas.my/id/eprint/34876/4/AUTOMATED%20PLANT%20DISEASE%20DETECTION%20USING%20DEEP%20LEARNING%20ON%20MOBILE%20PLATFORM.pdf
http://ir.unimas.my/id/eprint/34876/
_version_ 1811600352816922624
score 13.211869

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