Research review on intelligent object detection technology for coal mines based on deep learning
With the research and development of deep learning theory, object detection technology based on deep learning has made significant progress in the field of intelligent mining，which has become a typical paradigm and research hotspot of artificial intelligence technology in coal mining application sce...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Coal Science and Technology
2025-06-01
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| Series: | Meitan kexue jishu |
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| Online Access: | http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0428 |
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| author | Fan ZHANG Jiarong ZHANG Haixing CHENG |
| author_facet | Fan ZHANG Jiarong ZHANG Haixing CHENG |
| author_sort | Fan ZHANG |
| collection | DOAJ |
| description | With the research and development of deep learning theory, object detection technology based on deep learning has made significant progress in the field of intelligent mining，which has become a typical paradigm and research hotspot of artificial intelligence technology in coal mining application scenarios. However, deep learning object detection has a strong dependence on annotated datasets, and there are problems such as poor model interpretability and computational complexity. How to improve the accuracy, model adaptability, and computational efficiency of mine object detection is an urgent research topic in the field of mining artificial intelligence. The review is conducted on the intelligent object detection technology and its application research progress in underground coal mines. Firstly, a brief overview of object detection technology was provided, and the evolution process and algorithm classification of object detection technology based on deep learning were introduced. An analysis and comparison of object detection networks based on CNN and Transformer were also conducted. Then, key technologies such as data augmentation, super-resolution, and feature extraction for intelligent target detection in mines were studied, and the research progress of deep learning based-target detection in underground personnel safety monitoring, intelligent detection of mining equipment, and perception of working environment was elaborated in detail around the application requirements of “human machine environment” in coal mines. Finally, it was pointed out that there are still challenges in the construction of datasets, model optimization, and multi-source heterogeneous data fusion of intelligent target detection technology in coal mine application scenarios. The development trend of intelligent target detection technology in coal mines was discussed. It is proposed that in the future, object detection technology should be combined with small sample learning and multimodal fusion, model lightweight and edge computing, digital twins and embodied intelligence and other emerging technologies, so as to promote the deep integration and application of intelligent detection technology and coal mine safety production, and provide theoretical reference for the construction of mine intelligent object detection technology system. |
| format | Article |
| id | doaj-art-1f5f2cfe70cf45758cff48c93d69e064 |
| institution | Kabale University |
| issn | 0253-2336 |
| language | zho |
| publishDate | 2025-06-01 |
| publisher | Editorial Department of Coal Science and Technology |
| record_format | Article |
| series | Meitan kexue jishu |
| spelling | doaj-art-1f5f2cfe70cf45758cff48c93d69e0642025-08-20T03:27:47ZzhoEditorial Department of Coal Science and TechnologyMeitan kexue jishu0253-23362025-06-0153S128429610.12438/cst.2024-04282024-0428Research review on intelligent object detection technology for coal mines based on deep learningFan ZHANG0Jiarong ZHANG1Haixing CHENG2School of Artificial Intelligence, China University of Mining & Technology (Beijing), Beijing 100083, ChinaSchool of Artificial Intelligence, China University of Mining & Technology (Beijing), Beijing 100083, ChinaChina Coal Energy Research Institute Co., Ltd., Xi'an 710054, ChinaWith the research and development of deep learning theory, object detection technology based on deep learning has made significant progress in the field of intelligent mining，which has become a typical paradigm and research hotspot of artificial intelligence technology in coal mining application scenarios. However, deep learning object detection has a strong dependence on annotated datasets, and there are problems such as poor model interpretability and computational complexity. How to improve the accuracy, model adaptability, and computational efficiency of mine object detection is an urgent research topic in the field of mining artificial intelligence. The review is conducted on the intelligent object detection technology and its application research progress in underground coal mines. Firstly, a brief overview of object detection technology was provided, and the evolution process and algorithm classification of object detection technology based on deep learning were introduced. An analysis and comparison of object detection networks based on CNN and Transformer were also conducted. Then, key technologies such as data augmentation, super-resolution, and feature extraction for intelligent target detection in mines were studied, and the research progress of deep learning based-target detection in underground personnel safety monitoring, intelligent detection of mining equipment, and perception of working environment was elaborated in detail around the application requirements of “human machine environment” in coal mines. Finally, it was pointed out that there are still challenges in the construction of datasets, model optimization, and multi-source heterogeneous data fusion of intelligent target detection technology in coal mine application scenarios. The development trend of intelligent target detection technology in coal mines was discussed. It is proposed that in the future, object detection technology should be combined with small sample learning and multimodal fusion, model lightweight and edge computing, digital twins and embodied intelligence and other emerging technologies, so as to promote the deep integration and application of intelligent detection technology and coal mine safety production, and provide theoretical reference for the construction of mine intelligent object detection technology system.http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0428intelligent coal mineobject detectiondeep learningdigital twinembodied ai |
| spellingShingle | Fan ZHANG Jiarong ZHANG Haixing CHENG Research review on intelligent object detection technology for coal mines based on deep learning Meitan kexue jishu intelligent coal mine object detection deep learning digital twin embodied ai |
| title | Research review on intelligent object detection technology for coal mines based on deep learning |
| title_full | Research review on intelligent object detection technology for coal mines based on deep learning |
| title_fullStr | Research review on intelligent object detection technology for coal mines based on deep learning |
| title_full_unstemmed | Research review on intelligent object detection technology for coal mines based on deep learning |
| title_short | Research review on intelligent object detection technology for coal mines based on deep learning |
| title_sort | research review on intelligent object detection technology for coal mines based on deep learning |
| topic | intelligent coal mine object detection deep learning digital twin embodied ai |
| url | http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0428 |
| work_keys_str_mv | AT fanzhang researchreviewonintelligentobjectdetectiontechnologyforcoalminesbasedondeeplearning AT jiarongzhang researchreviewonintelligentobjectdetectiontechnologyforcoalminesbasedondeeplearning AT haixingcheng researchreviewonintelligentobjectdetectiontechnologyforcoalminesbasedondeeplearning |