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Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN)

Monitoring and understanding fish behavior is crucial to achieve precision in practices. The assessment of fish behavior has always been difficult due to the difference between aquaculture and experimental conditions and much sampling time taken. New technologies have been explored for this reason t...

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Main Authors: Wan Nur Azhani, Wan Samsudin, Mohd Harizan, Zul, Mohd Zamri, Ibrahim, Rohana, Abdul Karim, Wan Norhamidah, Wan Ibrahim
Format: Conference or Workshop Item
Language:English
English
Published: Institution of Engineering and Technology 2022
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TL Motor vehicles. Aeronautics. Astronautics
Online Access:http://umpir.ump.edu.my/id/eprint/42008/1/Zebrafish%20larvae%20locomotor%20activity%20detection.pdf
http://umpir.ump.edu.my/id/eprint/42008/2/Zebrafish%20larvae%20locomotor%20activity%20detection%20using%20Convolutional%20NeuraL%20Network%20%28CNN%29_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42008/
https://doi.org/10.1049/icp.2022.2583
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spelling my.ump.umpir.420082024-09-30T04:36:54Z http://umpir.ump.edu.my/id/eprint/42008/ Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN) Wan Nur Azhani, Wan Samsudin Mohd Harizan, Zul Mohd Zamri, Ibrahim Rohana, Abdul Karim Wan Norhamidah, Wan Ibrahim T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics Monitoring and understanding fish behavior is crucial to achieve precision in practices. The assessment of fish behavior has always been difficult due to the difference between aquaculture and experimental conditions and much sampling time taken. New technologies have been explored for this reason to get better fish behavior observation. However, most of it are high costing but still have limitations in monitoring the fish behavior. According to the studies, the changes in fish behavior may reflect to the changes of water quality. So, fish behavior can be a great indicator of water quality in aquaculture field. These reactions are also very important in behavioral neuroscience, which study on the physiological, genetic, and developmental mechanisms of behavior in humans and other animals. The zebrafish larvae are used as a model organism to examine the effects of neurotoxin to human behavior. To overcome the limitations, this works aims to develop an algorithm to elucidate the zebrafish larvae locomotor activity using Convolutional Neural Network (CNN). The model used for this project is ssd_mobilenet_v2 fpnlite and the result proved that it could detect the activity of zebrafish larvae with 99.05% of accuracy percentage. Institution of Engineering and Technology 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42008/1/Zebrafish%20larvae%20locomotor%20activity%20detection.pdf pdf en http://umpir.ump.edu.my/id/eprint/42008/2/Zebrafish%20larvae%20locomotor%20activity%20detection%20using%20Convolutional%20NeuraL%20Network%20%28CNN%29_ABS.pdf Wan Nur Azhani, Wan Samsudin and Mohd Harizan, Zul and Mohd Zamri, Ibrahim and Rohana, Abdul Karim and Wan Norhamidah, Wan Ibrahim (2022) Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN). In: IET Conference Proceedings. 2022 Engineering Technology International Conference, ETIC 2022 , 7 - 8 September 2022 , Kuantan, Virtual. pp. 130-135., 2022 (22). ISSN 2732-4494 ISBN 978-183953782-0 (Published) https://doi.org/10.1049/icp.2022.2583
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TL Motor vehicles. Aeronautics. Astronautics
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
TL Motor vehicles. Aeronautics. Astronautics
Wan Nur Azhani, Wan Samsudin
Mohd Harizan, Zul
Mohd Zamri, Ibrahim
Rohana, Abdul Karim
Wan Norhamidah, Wan Ibrahim
Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN)
description Monitoring and understanding fish behavior is crucial to achieve precision in practices. The assessment of fish behavior has always been difficult due to the difference between aquaculture and experimental conditions and much sampling time taken. New technologies have been explored for this reason to get better fish behavior observation. However, most of it are high costing but still have limitations in monitoring the fish behavior. According to the studies, the changes in fish behavior may reflect to the changes of water quality. So, fish behavior can be a great indicator of water quality in aquaculture field. These reactions are also very important in behavioral neuroscience, which study on the physiological, genetic, and developmental mechanisms of behavior in humans and other animals. The zebrafish larvae are used as a model organism to examine the effects of neurotoxin to human behavior. To overcome the limitations, this works aims to develop an algorithm to elucidate the zebrafish larvae locomotor activity using Convolutional Neural Network (CNN). The model used for this project is ssd_mobilenet_v2 fpnlite and the result proved that it could detect the activity of zebrafish larvae with 99.05% of accuracy percentage.
format Conference or Workshop Item
author Wan Nur Azhani, Wan Samsudin
Mohd Harizan, Zul
Mohd Zamri, Ibrahim
Rohana, Abdul Karim
Wan Norhamidah, Wan Ibrahim
author_facet Wan Nur Azhani, Wan Samsudin
Mohd Harizan, Zul
Mohd Zamri, Ibrahim
Rohana, Abdul Karim
Wan Norhamidah, Wan Ibrahim
author_sort Wan Nur Azhani, Wan Samsudin
title Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN)
title_short Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN)
title_full Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN)
title_fullStr Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN)
title_full_unstemmed Zebrafish larvae locomotor activity detection using Convolutional NeuraL Network (CNN)
title_sort zebrafish larvae locomotor activity detection using convolutional neural network (cnn)
publisher Institution of Engineering and Technology
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/42008/1/Zebrafish%20larvae%20locomotor%20activity%20detection.pdf
http://umpir.ump.edu.my/id/eprint/42008/2/Zebrafish%20larvae%20locomotor%20activity%20detection%20using%20Convolutional%20NeuraL%20Network%20%28CNN%29_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42008/
https://doi.org/10.1049/icp.2022.2583
_version_ 1822924680863940608
score 13.232414

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