孟加拉国淡水生态系统中鱼类物种识别的综合智能手机图像数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Saieef Sunny , Shiam Prodhan , Nazmuj Shakib , Mohammad Rifat Ahmmad Rashid , Nafees Mansoor
{"title":"孟加拉国淡水生态系统中鱼类物种识别的综合智能手机图像数据集","authors":"Saieef Sunny ,&nbsp;Shiam Prodhan ,&nbsp;Nazmuj Shakib ,&nbsp;Mohammad Rifat Ahmmad Rashid ,&nbsp;Nafees Mansoor","doi":"10.1016/j.dib.2025.111629","DOIUrl":null,"url":null,"abstract":"<div><div>The Bangladesh Fish Species Identification dataset encompasses 24,925 images representing 21 freshwater species commonly found in the rivers and ponds of Bangladesh. Photographs were taken using smartphones under carefully controlled conditions to ensure clarity and proper framing, and they include variations in lighting and background for realistic depiction. Species covered in this dataset include Aair, Boal, Chapila, DeshiPuti, Foli, Ilish, KalBaush, Katla, Koi, Magur, Mrigel, Pabda, Pangas, Puti, Rui, Shol, Shorputi, Taki, Tarabaim, Telapiya, and Tengra. By providing an extensive collection of labeled, high-quality images, this dataset serves as a valuable foundation for research on aquatic biodiversity, fishery management, and the development of precise machine-learning models for species recognition. It supports investigations into morphological variations, facilitates the evaluation of deep learning techniques, and assists in understanding fish distribution across diverse habitats.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"61 ","pages":"Article 111629"},"PeriodicalIF":1.0000,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive smartphone image dataset for fish species identification in Bangladesh's freshwater ecosystems\",\"authors\":\"Saieef Sunny ,&nbsp;Shiam Prodhan ,&nbsp;Nazmuj Shakib ,&nbsp;Mohammad Rifat Ahmmad Rashid ,&nbsp;Nafees Mansoor\",\"doi\":\"10.1016/j.dib.2025.111629\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The Bangladesh Fish Species Identification dataset encompasses 24,925 images representing 21 freshwater species commonly found in the rivers and ponds of Bangladesh. Photographs were taken using smartphones under carefully controlled conditions to ensure clarity and proper framing, and they include variations in lighting and background for realistic depiction. Species covered in this dataset include Aair, Boal, Chapila, DeshiPuti, Foli, Ilish, KalBaush, Katla, Koi, Magur, Mrigel, Pabda, Pangas, Puti, Rui, Shol, Shorputi, Taki, Tarabaim, Telapiya, and Tengra. By providing an extensive collection of labeled, high-quality images, this dataset serves as a valuable foundation for research on aquatic biodiversity, fishery management, and the development of precise machine-learning models for species recognition. It supports investigations into morphological variations, facilitates the evaluation of deep learning techniques, and assists in understanding fish distribution across diverse habitats.</div></div>\",\"PeriodicalId\":10973,\"journal\":{\"name\":\"Data in Brief\",\"volume\":\"61 \",\"pages\":\"Article 111629\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2025-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data in Brief\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352340925003609\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340925003609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

孟加拉国鱼类识别数据集包含24,925张图像,代表孟加拉国河流和池塘中常见的21种淡水物种。照片是在精心控制的条件下使用智能手机拍摄的,以确保清晰度和适当的框架,它们包括光线和背景的变化,以实现逼真的描绘。该数据集涵盖的物种包括Aair、Boal、Chapila、DeshiPuti、Foli、Ilish、KalBaush、Katla、Koi、Magur、Mrigel、Pabda、Pangas、Puti、Rui、Shol、Shorputi、Taki、Tarabaim、Telapiya和Tengra。通过提供大量标记的高质量图像,该数据集为水生生物多样性研究、渔业管理和开发用于物种识别的精确机器学习模型提供了宝贵的基础。它支持对形态变化的调查,促进深度学习技术的评估,并帮助了解鱼类在不同栖息地的分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comprehensive smartphone image dataset for fish species identification in Bangladesh's freshwater ecosystems
The Bangladesh Fish Species Identification dataset encompasses 24,925 images representing 21 freshwater species commonly found in the rivers and ponds of Bangladesh. Photographs were taken using smartphones under carefully controlled conditions to ensure clarity and proper framing, and they include variations in lighting and background for realistic depiction. Species covered in this dataset include Aair, Boal, Chapila, DeshiPuti, Foli, Ilish, KalBaush, Katla, Koi, Magur, Mrigel, Pabda, Pangas, Puti, Rui, Shol, Shorputi, Taki, Tarabaim, Telapiya, and Tengra. By providing an extensive collection of labeled, high-quality images, this dataset serves as a valuable foundation for research on aquatic biodiversity, fishery management, and the development of precise machine-learning models for species recognition. It supports investigations into morphological variations, facilitates the evaluation of deep learning techniques, and assists in understanding fish distribution across diverse habitats.
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
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
×
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