| アイテムタイプ |
共通アイテムタイプ(1) |
| 公開日 |
2025-01-30 |
| タイトル |
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|
タイトル |
Recognition of Fish in Aqua Cage by Machine Learning with Image Enhancement |
|
言語 |
en |
| その他のタイトル |
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その他のタイトル |
Recognition of fish in aqua cage by machine learning with image enhancement |
|
言語 |
en |
| 著者 |
Li, Zongru
Alraie, Hussam
Solpico, Dominic
西田, 祐也
石井, 和男
Yatsunami, Yoshinori
Fuchigami, Masanari
Suetsugu, Tokuo
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| 著作権関連情報 |
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|
権利情報 |
Copyright (c) 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
With the gradual decrease in fisheries resources and the increasing demand for fishery production, the production of capture fisheries is saturated. On the other hand, aquaculture production is increasing rapidly and now accounts for almost half of all fishery production. In aquaculture, monitoring aqua cages and collecting basic information, such as the number of fish in the cages and their sizes, is one of the most crucial tasks. However, automation of these basic tasks is insufficient, and there is an expectation for the implementation of ICT (Information and Communication Technology) in the fisheries industry. To move towards smart fishery farms, efficient fisheries resource management is required. This paper introduces a computer vision-based fish counting system that utilizes image enhancement and machine learning algorithms to achieve automated fish counting in aqua cages. Experimental results demonstrate that the proposed method can detect fish and identify the same fish in images captured by underwater cameras set at different depths. The proposed method can contribute to fisheries management and ecological conservation. |
|
言語 |
en |
| 備考 |
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|
内容記述タイプ |
Other |
|
内容記述 |
2024 16th IEEE/SICE International Symposium on System Integration, January 8 - 11, 2024, Ha Long, Vietnam |
|
言語 |
en |
| 書誌情報 |
en : 2024 IEEE/SICE International Symposium on System Integration (SII)
p. 637-643,
発行日 2024-02-09
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| 出版社 |
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出版者 |
IEEE |
| キーワード |
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主題Scheme |
Other |
|
主題 |
Intelligent fishery farm |
| キーワード |
|
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主題Scheme |
Other |
|
主題 |
underwater environment |
| キーワード |
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|
主題Scheme |
Other |
|
主題 |
Convolutional Neural Network |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
YOLO |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
image enhancement |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Counting |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| DOI |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
https://doi.org/10.1109/SII58957.2024.10417229 |
| ISBN |
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識別子タイプ |
ISBN |
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関連識別子 |
979-8-3503-1207-2 |
| 会議記述 |
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会議名 |
IEEE/SICE International Symposium on System Integration |
|
|
言語 |
en |
|
回次 |
16 |
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開始年 |
2024 |
|
|
開始月 |
01 |
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|
開始日 |
08 |
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終了年 |
2024 |
|
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終了月 |
01 |
|
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終了日 |
11 |
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開催国 |
VNM |
| 査読の有無 |
|
|
値 |
yes |
| 研究者情報 |
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URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/100000925_ja.html |
| 論文ID（連携） |
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|
値 |
10443624 |
| 連携ID |
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|
値 |
12541 |
10443624.pdf (796 KB)
