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印度海鲜市场的物种识别:使用鱼类数据集的机器学习方法

Priyanka Paygude¹, Namita Shinde¹, Amol Dhumane²

¹Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.

|January 13, 2025

概括

一个由8488张图像组成的新数据集,为机器学习应用提供了八种印度鱼类的关键特征. 该资源有助于开发AI模型,用于印度海鲜行业的物种识别.

科学领域:

海洋生物学海洋生物学
计算机科学计算机科学
数据科学数据科学数据科学

背景情况:

印度海鲜产业在经济上具有重要意义,对技术进步的需求日益增长.
准确的鱼类物种识别对于贸易,管理和研究至关重要.

研究的目的:

为机器学习引入印度海鱼图像的全面,精心策划的数据集.
支持为印度海鲜市场开发AI驱动的解决方案.

主要方法:

获取和整理了8488张图像,涵盖了八种商业上重要的印度鱼类.
数据采集过程和元数据结构的详细文档,以提高可用性.

主要成果:

一个高质量的数据集,包含8488张图像,代表八种不同的鱼类.
数据集包括科学和当地名称,促进更广泛的可访问性.

结论:

这一数据集为推进印度海鲜行业机器学习应用提供了基础资源.
它允许开发可靠的模型,用于自动识别鱼类物种和相关任务.

关键词:

鱼类的分类鱼类的分类鱼类数据集鱼类数据集鱼类检测器鱼类检测器机器学习是机器学习.

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