Dried fish dataset for Indian seafood: A machine learning application

被引:8
作者
Paygude, Priyanka [1 ]
Gayakwad, Milind [1 ]
Wategaonkar, Dhanashri [2 ]
Pawar, Rajendra [3 ]
Pujeri, Ramchandra [3 ]
Joshi, Rahul [4 ]
机构
[1] Bharati Vidyapeeth, Coll Engn, Pune, India
[2] Dr Vishwanath Karad MIT World Peace Univ, Dept Comp Engn & Technol, Pune, India
[3] MIT Art Design & Technol Univ, MIT Sch Comp, Pune, India
[4] Symbiosis Int, Symbiosis Inst Technol, Pune, India
关键词
Dried fish classification; Dried fish dataset; Dried fish detection; Machine learning;
D O I
10.1016/j.dib.2024.110563
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Dryingfish is a simple and economical way to process the catch. It creates a profitable business for coastal communities by providing a market for their catches, even during periods of abundance. It's a traditional method to preserve fish, especially valuable in regions where fresh fish isn't readily available or affordable throughout the year. This dataset provides a rich resource of 8290 images specifically designed for machine learning applications. It focuses on the five most popular types of dried seafood in India: prawns (shrimp), small anchovies (tingali), golden anchovies (mandeli), mackerel (bangada), and Bombay duck (bombil). To ensure high-quality data for machine learning applications for Identification and classification of different dried fish varieties, the dataset features a diverse set of images in singles and in bulk for each category. The dataset utilizes standardized lighting, background, and object pose for optimal machine learning performance. This rich dataset empowers researchers and data scientists to leverage machine learning for various applications in the Indian dried fish industry.Overall, the Dried Fish Dataset for Indian Seafood aims to leverage machine learning to improve the standardization, quality control, safety, and efficiency of the Indian dried fish industry. (c) 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
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页数:8
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