Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar

Effective detection of diseases in aquaculture is important for maintaining fish populations and encouraging appropriate practices. Traditional approaches frequently depend on visual inspection without any tools which can be difficult in terms of precision and productivity. This study presents a fis...

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Bibliographic Details
Main Author:	Azahar, Nur Adriana Qaisara
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Neural networks (Computer science)
Online Access:	https://ir.uitm.edu.my/id/eprint/96037/1/96037.pdf
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id	my-uitm-ir.96037
record_format	uketd_dc
spelling	my-uitm-ir.960372024-05-28T15:34:17Z Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar 2024 Azahar, Nur Adriana Qaisara Neural networks (Computer science) Effective detection of diseases in aquaculture is important for maintaining fish populations and encouraging appropriate practices. Traditional approaches frequently depend on visual inspection without any tools which can be difficult in terms of precision and productivity. This study presents a fish detection system that uses Convolutional Neural Networks (CNNs) and advanced image processing techniques, with a flexible research approach directing the iterative development process. The CNN model, chosen by algorithmic analysis, shows an impressive accuracy of 90% in automatically recognizing and diagnosing different fish diseases. By being trained on several datasets, the model can identify important features from images of fish. A program that is easy to use is then created for aquaculture professionals, allowing for quick and accurate disease diagnosis. This method represents a notable advancement in utilizing machine learning for disease control in aquaculture, surpassing the limitations of manual observation and contributing to the sustainable future of fish farming industries. 2024 Thesis https://ir.uitm.edu.my/id/eprint/96037/ https://ir.uitm.edu.my/id/eprint/96037/1/96037.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Media Abdul Hamid, Nor Hasnul Azirah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abdul Hamid, Nor Hasnul Azirah
topic	Neural networks (Computer science)
spellingShingle	Neural networks (Computer science) Azahar, Nur Adriana Qaisara Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar
description	Effective detection of diseases in aquaculture is important for maintaining fish populations and encouraging appropriate practices. Traditional approaches frequently depend on visual inspection without any tools which can be difficult in terms of precision and productivity. This study presents a fish detection system that uses Convolutional Neural Networks (CNNs) and advanced image processing techniques, with a flexible research approach directing the iterative development process. The CNN model, chosen by algorithmic analysis, shows an impressive accuracy of 90% in automatically recognizing and diagnosing different fish diseases. By being trained on several datasets, the model can identify important features from images of fish. A program that is easy to use is then created for aquaculture professionals, allowing for quick and accurate disease diagnosis. This method represents a notable advancement in utilizing machine learning for disease control in aquaculture, surpassing the limitations of manual observation and contributing to the sustainable future of fish farming industries.
format	Thesis
qualification_level	Bachelor degree
author	Azahar, Nur Adriana Qaisara
author_facet	Azahar, Nur Adriana Qaisara
author_sort	Azahar, Nur Adriana Qaisara
title	Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar
title_short	Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar
title_full	Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar
title_fullStr	Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar
title_full_unstemmed	Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar
title_sort	fish disease detection using convolutional neural network (cnn) / nur adriana qaisara azahar
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Media
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/96037/1/96037.pdf
_version_	1804889978276151296

Fish disease detection using Convolutional Neural Network (CNN) / Nur Adriana Qaisara Azahar

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