Mine 4.0-mineCareerDB: A high-resolution image dataset for mining career segmentation and object detection

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2024-10-01 DOI:10.1016/j.dib.2024.110976

Nasreddine Haqiq , Mounia Zaim , Mohamed Sbihi , Khalid El Amraoui , Mustapha El Alaoui , Lhoussaine Masmoudi , Hamza Echarrafi

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引用次数: 0

Abstract

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

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Mine 4.0-mineCareerDB：用于采矿职业细分和对象检测的高分辨率图像数据集

文章介绍了 Mine 4.0-MineCareerDB，这是一个公开可用的高分辨率图像数据集，由大疆 Phantom 4 RTK 无人机拍摄，专门用于分析采矿职业。该数据集由 373 幅描绘各种采矿作业和活动的图像组成。每张图像都有地理坐标，可提供采矿活动的详细情况，包括各种设备的使用、基础设施和整体采矿环境。该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采矿作业自动化研究。通过公开 Mine4.0-MineCareerDB，我们希望进一步推动计算机视觉研究及其在采矿业的应用。数据集可从以下网址获取： https://data.mendeley.com/datasets/c5s76mj4bm/5

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.