WEKO3
アイテム
Identification of Fish Species using Neural Networks
https://fra.repo.nii.ac.jp/records/2011928
https://fra.repo.nii.ac.jp/records/2011928dd95c267-9c2b-41ac-8044-82462bc2c366
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
fishu_k_58_65.pdf (1.2 MB)
|
.png)
|
| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2024-10-11 | |||||
| タイトル | ||||||
| タイトル | Identification of Fish Species using Neural Networks | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Fishery engineering; Species identification; Neural network; Truss protocol | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | departmental bulletin paper | |||||
| アクセス権 | ||||||
| アクセス権 | open access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
| 著者 |
森元, 映治
× 森元, 映治× 平, 雄一郎× 中村, 誠 |
|||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | The number of workers engaged in Japanese fisheries and related industries in Japan has decreased markedly in recent years due to factors such as an aging workforce, issues related to the management of natural resources and the environment, international affairs, and changes in consumer food preferences. There is therefore a need to mechanize and automate aspects related to work usually performed by humans in the fishery industry. In this research, a system for identifying fish species has been developed. The system employs neural networks which learn to differentiate between different fish species using reference points. Reference points are characteristic points that are extracted from images of the body surface of the fish using a method that employs the truss protocol. The ratios of specific truss lengths between reference points relative to total body length are used to compile the dataset used for network inputs. For fish with bodies that have been contorted, only data from the vicinity of the fish head are used for network learning. Given that body color is an important characteristic for species identification, an effective method for capturing color data was investigated and the effectiveness of the proposed method and optimal number of color parameters was determined. | |||||
| 言語 | en | |||||
| 書誌情報 |
ja : 水産大学校研究報告 en : Journal of National Fisheries University 巻 58, 号 1, p. 65-71, ページ数 7, 発行日 2009-11 |
|||||
| 出版者 | ||||||
| 出版者 | 水産大学校 | |||||
| 言語 | ja | |||||
| 出版者 | ||||||
| 出版者 | National Fisheries University | |||||
| 言語 | en | |||||
| ISSN | ||||||
| 収録物識別子タイプ | PISSN | |||||
| 収録物識別子 | 0370-9361 | |||||
| 書誌レコードID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AN00124678 | |||||
| 情報源 | ||||||
| 識別子タイプ | Local | |||||
| 関連識別子 | fishu_k_58_65 | |||||
