摘要
为加强对自然资源勘查开发活动的监督管理,提升自然资源监管能力和水平,文章深入剖析了传统自然资源监管体系的不足。在此基础上,提出借助铁塔高点监控的优势,针对违法采矿过程中使用的施工机械,优化深度学习目标检测算法模型。通过对可疑图片采取放大二次检测的方式,提升算法识别的准确性和效率。该项目目前已深度融入矿产卫片执法的工作机制中,大大提升了对监控区域内矿产资源违法行为的识别与制止能力。
In order to strengthen the supervision and management of natural resources exploration and development activities and improve the ability and level of natural resources supervision,this paper deeply analyzes the shortcomings of the traditional natural resources supervision system.On this basis,it is proposed to optimize the Deep Learning target detection algorithm model for the construction machinery used in the illegal mining process by virtue of the advantages of tower high point supervision.The accuracy and efficiency of the algorithm recognition are improved by enlarging the secondary detection of suspicious images.The project has been deeply integrated into the working mechanism of mineral satellite image law enforcement,which greatly improves the ability to identify and stop illegal acts of mineral resources in the supervision area.
作者
林宏
LIN Hong(Fujian Branch of China Tower Co.,Ltd.,Fuzhou 350007,China)
出处
《现代信息科技》
2025年第6期189-193,198,共6页
Modern Information Technology
关键词
视频监控
矿产资源
高点监控
自然资源
video surveillance
mineral resource
high point supervision
natural resource
作者简介
林宏(1984-),男,汉族,福建福州人,高级工程师,硕士,研究方向:计算机网络、计算机应用、信息系统。
