首页|基于国产高分大数据和深度学习的北方露天煤矿识别

基于国产高分大数据和深度学习的北方露天煤矿识别

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如何实时、高效地对煤矿进行监测、规范煤矿管理以及煤矿潜在危险监测已经成为矿产行业愈发关注的一个问题.本文以内蒙古自治区、新疆维吾尔自治区和山西省露天煤矿为研究区域,使用国产高分辨率遥感卫星影像数据,构建露天煤矿的样本数据集,利用卷积神经网络,训练并且测试了针对于国产高分遥感数据的露天煤矿提取模型,实现了对研究区域内露天煤矿的自动提取.
Identification of Northern Open-pit Coal Mine Based on Domestic High Score Big Data and Deep Learning
How to monitor the coal mine in real time and efficiently,standardize the coal mine management and monitor the potential danger in coal mine has become a problem that the mining industry pays more and more attention to.This paper takes open-pit coal mines in Inner Mongolia Autonomous Region,Xinjiang Uygur Autonomous Region and Shanxi Province as research areas,uses high-resolution remote sensing satellite image data from China to build sample data sets of open-pit coal mines,and uses convolutional neural network to train and test the open-pit coal mine extraction model based on high-resolution remote sensing data from China,realizing automatic extraction of open-pit coal mines in the study area.

MASK R-CNNopen-pit coal minehigh-resolution remote sensing imagedeep learning

刘锐

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北京建筑大学测绘与城市空间信息学院,北京

MASK R-CNN 露天煤矿 高分辨率遥感影像 深度学习

2024

科学技术创新
黑龙江省科普事业中心

科学技术创新

影响因子:0.842
ISSN:1673-1328
年,卷(期):2024.(9)
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