Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data
The Indian sea fish market is a dynamic and significant sector, contributing to both the domestic economy and the global seafood trade. This fish dataset is specifically curated for machine learning applications in the Indian seafood industry. It includes a comprehensive collection of images represe...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340924011715 |
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| author | Priyanka Paygude Namita Shinde Amol Dhumane Geeta S. Navale Prashant Chavan Atul Kathole Vijaykumar Bidve |
| author_facet | Priyanka Paygude Namita Shinde Amol Dhumane Geeta S. Navale Prashant Chavan Atul Kathole Vijaykumar Bidve |
| author_sort | Priyanka Paygude |
| collection | DOAJ |
| description | The Indian sea fish market is a dynamic and significant sector, contributing to both the domestic economy and the global seafood trade. This fish dataset is specifically curated for machine learning applications in the Indian seafood industry. It includes a comprehensive collection of images representing eight commercially significant fish species native to Indian waters, comprising a total of 8488 images. This dataset serves as a valuable resource for developing and refining machine learning models in the domain. It focuses on the eight most widely consumed fish species in India: Pomfret (scientific name: Pampus argeneus, local name: Paplet), Mackerel (scientific name: Scomber scombrus, local name: Bangda), Black Snapper (scientific name: Apsilus dentatus, local name: Tilapia), Indian Carp (scientific name: Cyprinus carpio, local name: Rohu), Prawn (scientific name: Dendrobranchiata, local name: Kolambi), Pink Perch (scientific name: Zalembius rosaceus, local name: Rani Fish), Indian flathead (scientific name: Lates calcarifer, local name: Bhetki Fish) and Black Pomfret (scientific name: Parastromateus niger, local name: Black Paplet). Article details the data acquisition process, and metadata structure, ensuring accessibility and usability for researchers and industry professionals. This resource facilitates the development of machine learning models for tasks such as species identification within the Indian seafood industry. |
| format | Article |
| id | doaj-art-d3ded6879ddc40dc8da5c4d04347783e |
| institution | Kabale University |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-d3ded6879ddc40dc8da5c4d04347783e2025-01-31T05:11:30ZengElsevierData in Brief2352-34092025-02-0158111209Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley DataPriyanka Paygude0Namita Shinde1Amol Dhumane2Geeta S. Navale3Prashant Chavan4Atul Kathole5Vijaykumar Bidve6Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India; Corresponding author.Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, IndiaSymbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, IndiaSinhgad Institute of Technology and Science, Pune, IndiaBharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, IndiaDr. D. Y. Patil Institute of Technology, Pimpri, Pune, IndiaSchool of CSIT, Symbiosis Skills and Professional University, Kiwale, Pune, IndiaThe Indian sea fish market is a dynamic and significant sector, contributing to both the domestic economy and the global seafood trade. This fish dataset is specifically curated for machine learning applications in the Indian seafood industry. It includes a comprehensive collection of images representing eight commercially significant fish species native to Indian waters, comprising a total of 8488 images. This dataset serves as a valuable resource for developing and refining machine learning models in the domain. It focuses on the eight most widely consumed fish species in India: Pomfret (scientific name: Pampus argeneus, local name: Paplet), Mackerel (scientific name: Scomber scombrus, local name: Bangda), Black Snapper (scientific name: Apsilus dentatus, local name: Tilapia), Indian Carp (scientific name: Cyprinus carpio, local name: Rohu), Prawn (scientific name: Dendrobranchiata, local name: Kolambi), Pink Perch (scientific name: Zalembius rosaceus, local name: Rani Fish), Indian flathead (scientific name: Lates calcarifer, local name: Bhetki Fish) and Black Pomfret (scientific name: Parastromateus niger, local name: Black Paplet). Article details the data acquisition process, and metadata structure, ensuring accessibility and usability for researchers and industry professionals. This resource facilitates the development of machine learning models for tasks such as species identification within the Indian seafood industry.http://www.sciencedirect.com/science/article/pii/S2352340924011715Fish classificationFish datasetFish detectionMachine learning |
| spellingShingle | Priyanka Paygude Namita Shinde Amol Dhumane Geeta S. Navale Prashant Chavan Atul Kathole Vijaykumar Bidve Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data Data in Brief Fish classification Fish dataset Fish detection Machine learning |
| title | Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data |
| title_full | Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data |
| title_fullStr | Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data |
| title_full_unstemmed | Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data |
| title_short | Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data |
| title_sort | species identification for indian seafood markets a machine learning approach with a fish datasetmendeley data |
| topic | Fish classification Fish dataset Fish detection Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2352340924011715 |
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