Haqiq Nasreddine, Zaim Mounia, Sbihi Mohamed, Amraoui Khalid El, Alaoui Mustapha El, Masmoudi Lhoussaine, Echarrafi Hamza
Laboratory of Systems Analysis, Information Processing and Industrial Management (LASTIMI), High School of Technology of Salé, Mohammed V University in Rabat, Rabat, Morocco.
LCS Laboratory, Physics Department Faculty of Science, Mohammed V University in Rabat, Rabat, Morocco.
Data Brief. 2024 Oct 1;57:110976. doi: 10.1016/j.dib.2024.110976. eCollection 2024 Dec.
The article presents Mine 4.0-MineCareerDB, a publicly available dataset of high-resolution image captured by a DJI Phantom 4 RTK drone specifically designed for analyzing mining careers. The dataset comprises a collection of 373 images depicting various mining operations and activities. Each image is georeferenced and offers a detailed view of mining activities, including the use of various equipment, infrastructure, and overall mining environment. This dataset has the potential to be a valuable resource for computer vision applications in the mining industry such as developing algorithms for identifying mining equipment, training deep learning models for safety analysis and optimization, and research on automation in mining operations. By making Mine4.0-MineCareerDB publicly available, we aim to stimulate further advancements in computer vision research and its applications in the mining sector. The dataset is available at: https://data.mendeley.com/datasets/c5s76mj4bm/5.
本文介绍了Mine 4.0-MineCareerDB，这是一个可公开获取的数据集，由DJI Phantom 4 RTK无人机拍摄的高分辨率图像组成，专门用于分析采矿职业。该数据集包含373张描绘各种采矿作业和活动的图像。每张图像都进行了地理配准，并提供了采矿活动的详细视图，包括各种设备的使用、基础设施以及整体采矿环境。这个数据集有可能成为采矿业计算机视觉应用的宝贵资源，例如开发用于识别采矿设备的算法、训练用于安全分析和优化的深度学习模型，以及研究采矿作业的自动化。通过公开Mine4.0-MineCareerDB，我们旨在推动计算机视觉研究及其在采矿领域应用的进一步发展。该数据集可在以下网址获取：https://data.mendeley.com/datasets/c5s76mj4bm/5 。
