Cars Overhead with Context (COWC)
收藏arXiv2016-09-15 更新2024-06-21 收录
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http://gdodatasci.ucllnl.org/cowc/
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资源简介：
Cars Overhead with Context (COWC) 数据集是由劳伦斯利弗莫尔国家实验室计算工程部门创建的大型多样化汽车数据集，包含32,716个独特的汽车图像，这些图像来自六个不同的地理区域，由不同的成像设备生成。数据集旨在通过包含上下文信息来帮助识别困难目标，如船只、拖车、灌木和空调单元等易与汽车混淆的物体。数据集的应用领域包括商业和政府目的，如停车场车辆计数和交通流量监控，旨在解决大规模标准化公共数据集的缺乏问题。
Cars Overhead with Context (COWC) dataset was created by the Computational Engineering Division of Lawrence Livermore National Laboratory. It is a large-scale, diverse automotive dataset containing 32,716 unique car images sourced from six distinct geographic regions and generated by various imaging devices. The dataset is designed to aid in the recognition of challenging targets that are easily misclassified as cars, including vessels, trailers, shrubs, and air conditioning units, by incorporating contextual information. It has applications across commercial and governmental use cases, such as parking lot vehicle counting and traffic flow monitoring, and was developed to address the scarcity of large-scale standardized public datasets.
提供机构：
劳伦斯利弗莫尔国家实验室计算工程部门
创建时间：
2016-09-15
