Bufotes viridis balearicus(Boettger,1880 年)背部的个体颜色图案可用于种群研究的个体照片识别。

IF 1 4区 生物学 Q3 ZOOLOGY
N. Lassnig, Sergi Guasch-Martínez, Samuel Pinya Fernández
{"title":"Bufotes viridis balearicus(Boettger,1880 年)背部的个体颜色图案可用于种群研究的个体照片识别。","authors":"N. Lassnig, Sergi Guasch-Martínez, Samuel Pinya Fernández","doi":"10.1139/cjz-2023-0019","DOIUrl":null,"url":null,"abstract":"This study explores the potential of Photo-Identification Methods (PIM) as a viable, noninvasive, and ethical tool for wildlife studies, with a specific focus on anuran species such as Bufotes viridis balearicus (Boettger, 1880). Although the Automatic Photo Identification Suit (APHIS) software was initially designed for lizard identification, our research shows its adaptability for anuran species, achieving a high detection accuracy rate of 95.28%. Thus, obtaining outstanding and higher values comparing to previous studies on this species. Crucially, our findings indicate that the success of PIM and the efficacy of image identification software like APHIS is dependent on the quality and standardization of the images collected. The study also underscores the importance of practical experience and continuous learning for the optimal utilization of software like APHIS. Despite occasional False Rejected Matches (FRM), the overall strong performance metrics with low False Rejection Rate (FRR) demonstrate that these instances do not significantly impact the reliability of the technique. Thus, this research highlights the importance of careful implementation, continuous learning, and image quality control in leveraging the full potential of image identification software in wildlife studies.","PeriodicalId":9484,"journal":{"name":"Canadian Journal of Zoology","volume":"11 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The individual color pattern on the back of Bufotes viridis balearicus (Boettger, 1880) allows individual photo identification recognition for population studies.\",\"authors\":\"N. Lassnig, Sergi Guasch-Martínez, Samuel Pinya Fernández\",\"doi\":\"10.1139/cjz-2023-0019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study explores the potential of Photo-Identification Methods (PIM) as a viable, noninvasive, and ethical tool for wildlife studies, with a specific focus on anuran species such as Bufotes viridis balearicus (Boettger, 1880). Although the Automatic Photo Identification Suit (APHIS) software was initially designed for lizard identification, our research shows its adaptability for anuran species, achieving a high detection accuracy rate of 95.28%. Thus, obtaining outstanding and higher values comparing to previous studies on this species. Crucially, our findings indicate that the success of PIM and the efficacy of image identification software like APHIS is dependent on the quality and standardization of the images collected. The study also underscores the importance of practical experience and continuous learning for the optimal utilization of software like APHIS. Despite occasional False Rejected Matches (FRM), the overall strong performance metrics with low False Rejection Rate (FRR) demonstrate that these instances do not significantly impact the reliability of the technique. Thus, this research highlights the importance of careful implementation, continuous learning, and image quality control in leveraging the full potential of image identification software in wildlife studies.\",\"PeriodicalId\":9484,\"journal\":{\"name\":\"Canadian Journal of Zoology\",\"volume\":\"11 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Journal of Zoology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1139/cjz-2023-0019\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ZOOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Zoology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1139/cjz-2023-0019","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ZOOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

本研究探讨了照片识别方法(PIM)作为一种可行的、非侵入性的、符合道德规范的野生动物研究工具的潜力,重点关注无尾类物种,如 Bufotes viridis balearicus(Boettger,1880 年)。虽然自动照片识别套装(APHIS)软件最初是为蜥蜴识别而设计的,但我们的研究表明,它适用于无尾类物种,检测准确率高达 95.28%。因此,与以前对该物种的研究相比,我们获得了更高的准确率。最重要的是,我们的研究结果表明,PIM 的成功和 APHIS 等图像识别软件的功效取决于所采集图像的质量和标准化程度。这项研究还强调了实践经验和不断学习对于优化使用 APHIS 等软件的重要性。尽管偶尔会出现错误拒绝匹配 (FRM),但整体性能指标很高,错误拒绝率 (FRR) 很低,这表明这些情况不会对该技术的可靠性产生重大影响。因此,这项研究强调了在野生动物研究中充分发挥图像识别软件的潜力时,认真实施、不断学习和图像质量控制的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The individual color pattern on the back of Bufotes viridis balearicus (Boettger, 1880) allows individual photo identification recognition for population studies.
This study explores the potential of Photo-Identification Methods (PIM) as a viable, noninvasive, and ethical tool for wildlife studies, with a specific focus on anuran species such as Bufotes viridis balearicus (Boettger, 1880). Although the Automatic Photo Identification Suit (APHIS) software was initially designed for lizard identification, our research shows its adaptability for anuran species, achieving a high detection accuracy rate of 95.28%. Thus, obtaining outstanding and higher values comparing to previous studies on this species. Crucially, our findings indicate that the success of PIM and the efficacy of image identification software like APHIS is dependent on the quality and standardization of the images collected. The study also underscores the importance of practical experience and continuous learning for the optimal utilization of software like APHIS. Despite occasional False Rejected Matches (FRM), the overall strong performance metrics with low False Rejection Rate (FRR) demonstrate that these instances do not significantly impact the reliability of the technique. Thus, this research highlights the importance of careful implementation, continuous learning, and image quality control in leveraging the full potential of image identification software in wildlife studies.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Canadian Journal of Zoology
Canadian Journal of Zoology 生物-动物学
CiteScore
2.40
自引率
0.00%
发文量
82
审稿时长
3 months
期刊介绍: Published since 1929, the Canadian Journal of Zoology is a monthly journal that reports on primary research contributed by respected international scientists in the broad field of zoology, including behaviour, biochemistry and physiology, developmental biology, ecology, genetics, morphology and ultrastructure, parasitology and pathology, and systematics and evolution. It also invites experts to submit review articles on topics of current interest.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信