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DWSD:密集废物细分数据集

Asfak Ali¹, Suvojit Acharjee², Md Manarul Sk¹

¹Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata 700032, India.

|February 25, 2025

概括

本研究引入了一个新的数据集,以增强自动废物细分系统. 该数据集有助于开发更好的回收技术,通过从注释图像分类14种废物类型.

科学领域:

计算机科学计算机科学
环境科学环境科学
数据科学数据科学数据科学

背景情况:

垃圾处理是一个重要的全球问题,特别是在城市地区.
有效的废物分离对于回收和资源管理至关重要.
与自动化系统相比,目前的手动废物分离方法效率低下.

研究的目的:

提出一套新的,手动注释的数据集,以改进自动废物细分.
支持先进废物分类技术的发展.
为了解决发展中国家手工垃圾分类的局限性.

主要方法:

收集了Jadavpur大学周围各个地点的784张废物图像.
使用Labelme程序手动注释图像,创建颜色注释.
废物被分为14个不同的类别,包括塑料,纸张,玻璃和金属.

主要成果:

该数据集包含 784 个图像与 2350 个对象段.
附注涵盖了14个不同的废物类别,促进了详细的分类.
数据集的格式是用于用于废物细分的机器学习模型的训练.

结论:

开发的数据集是推动废物自动化细分的宝贵资源.
这种资源可以为提高回收效率和废物管理策略做出重大贡献.
该数据集为未来对智能废物管理系统的研究提供了基础.

关键词:

分类和细分是如何进行的.计算机视觉计算机视觉计算机视觉智慧城市是智慧城市.废物管理废物管理

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