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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Recognition Methods for Coal and Coal Gangue Based on Deep Learning
Qiang Liu, Li Jingao, Yusheng Li, et al.
IEEE Access (2021) Vol. 9, pp. 77599-77610
Open Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

Research on lightweight Yolo coal gangue detection algorithm based on resnet18 backbone feature network
Guanghui Xue, Sanxi Li, Peng Hou, et al.
Internet of Things (2023) Vol. 22, pp. 100762-100762
Open Access | Times Cited: 41
A high-confidence instance boundary regression approach and its application in coal-gangue separation
Ziqi Lv, Weidong Wang, Kanghui Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 132, pp. 107894-107894
Closed Access | Times Cited: 12
Research and prospect of underground intelligent coal gangue sorting technology: A review
Guozhen Zhao, Fengyi Chang, Jiaxin Chen, et al.
Minerals Engineering (2024) Vol. 215, pp. 108818-108818
Closed Access | Times Cited: 10
Intelligent photoelectric identification of coal and gangue − A review
Jianqiang Yin, Jinbo Zhu, Hongzheng Zhu, et al.
Measurement (2024) Vol. 233, pp. 114723-114723
Closed Access | Times Cited: 8
Study of raw coal identification method by dual-energy X-ray and dual-view visible light imaging
Lei He, Shuang Wang, Yongcun Guo, et al.
International Journal of Coal Preparation and Utilization (2022) Vol. 43, Iss. 2, pp. 361-376
Closed Access | Times Cited: 25
Investigating comparisons on the coal and gangue in various scenarios using multidimensional image features
Ziqi Lv, Yao Cui, Kanghui Zhang, et al.
Minerals Engineering (2023) Vol. 204, pp. 108450-108450
Closed Access | Times Cited: 14
A high accuracy detection method for coal and gangue with S3DD-YOLOv8
Fangfang Xin, Qianguo Jia, Yong Yang, et al.
International Journal of Coal Preparation and Utilization (2024), pp. 1-19
Closed Access | Times Cited: 5
STATNet: One-stage coal-gangue detector based on deep learning algorithm for real industrial application
Kefei Zhang, Teng Wang, Xiaolin Yang, et al.
Energy and AI (2024) Vol. 17, pp. 100388-100388
Open Access | Times Cited: 5
Data-driven model SSD-BSP for multi-target coal-gangue detection
Luyao Wang, Xuewen Wang, Bo Li
Measurement (2023) Vol. 219, pp. 113244-113244
Closed Access | Times Cited: 13
Coal Gangue Target Detection Based on Improved YOLOv5s
Shuxiao Wang, Jiandong Zhu, Zuotao Li, et al.
Applied Sciences (2023) Vol. 13, Iss. 20, pp. 11220-11220
Open Access | Times Cited: 12
A near-infrared spectroscopy dataset of coal and coal-measure rock under diverse conditions
Yuanbo Lv, Shibo Wang, En Yang, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 4
A Big Coal Block Alarm Detection Method for Scraper Conveyor Based on YOLO-BS
Yuan Wang, Wei Guo, Shuanfeng Zhao, et al.
Sensors (2022) Vol. 22, Iss. 23, pp. 9052-9052
Open Access | Times Cited: 19
Coal Gangue Classification Based on the Feature Extraction of the Volume Visual Perception ExM-SVM
Murad Saleh Alfarzaeai, Eryi Hu, Peng Wang, et al.
Energies (2023) Vol. 16, Iss. 4, pp. 2064-2064
Open Access | Times Cited: 10
A deep learning method based on multi-scale fusion for noise-resistant coal-gangue recognition
Qingjun Song, Shirong Sun, Qinghui Song, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A large-scale open image dataset for deep learning-enabled intelligent sorting and analyzing of raw coal
Ziqi Lv, Yuhan Fan, Te Sha, et al.
Scientific Data (2025) Vol. 12, Iss. 1
Open Access
Lightweight coal and gangue detection algorithm based on LTC-Yolov8n
Ruizhe Liu, Chuanhua Wei
International Journal of Coal Preparation and Utilization (2025), pp. 1-19
Closed Access
Turning Trash into Treasure: Silicon Carbide Nanoparticles from Coal Gangue and High-Carbon Waste Materials
Kun Gao, Yao Zhang, Binghan Wang, et al.
Molecules (2025) Vol. 30, Iss. 7, pp. 1562-1562
Open Access
YOLOv8-POS: a lightweight model for coal-rock image recognition
Zhao Yan-qin, Wenyu Wang
PeerJ Computer Science (2025) Vol. 11, pp. e2820-e2820
Open Access
Improved mask R-CNN-based instance segmentation model for coal gangue
Ping Sun, Weimin Wu
International Journal of Coal Preparation and Utilization (2025), pp. 1-19
Closed Access
Lightweight Target Detection for Coal and Gangue Based on Improved Yolov5s
Zhenguan Cao, Liao Fang, Zhuoqin Li, et al.
Processes (2023) Vol. 11, Iss. 4, pp. 1268-1268
Open Access | Times Cited: 9
Image Recognition of Mine Water Inrush Based on Bilinear Convolutional Neural Network with Few-Shot Learning
Shuai Zhang, Yuanze Du, Yingwang Zhao, et al.
ACS Omega (2024) Vol. 9, Iss. 10, pp. 12027-12036
Open Access | Times Cited: 3
Research on coal and gangue segmentation based on MFCCM‐Mask R‐CNN
Zhenguan Cao, Zhuoqin Li, Liao Fang, et al.
Energy Science & Engineering (2024) Vol. 12, Iss. 7, pp. 2958-2973
Open Access | Times Cited: 3
A Coal Gangue Identification Method Based on HOG Combined with LBP Features and Improved Support Vector Machine
Gang Cheng, Jie Chen, Yifan Wei, et al.
Symmetry (2023) Vol. 15, Iss. 1, pp. 202-202
Open Access | Times Cited: 8
Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review
Yuxin Du, He Zhang, Liang Liang, et al.
IEEE Access (2023) Vol. 11, pp. 102871-102898
Open Access | Times Cited: 8
Utilizing semantic-level computer vision for fracture trace characterization of hard rock pillars in underground space
Chuanqi Li, Jian Zhou, Daniel Dias
Geoscience Frontiers (2023) Vol. 15, Iss. 2, pp. 101769-101769
Open Access | Times Cited: 8
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