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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:

An Image-Based Hierarchical Deep Learning Framework for Coal and Gangue Detection
Dongjun Li, Zhenxin Zhang, Zhihua Xu, et al.
IEEE Access (2019) Vol. 7, pp. 184686-184699
Open Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Fast identification model for coal and gangue based on the improved tiny YOLO v3
Hongguang Pan, Yuhong Shi, Xinyu Lei, et al.
Journal of Real-Time Image Processing (2022) Vol. 19, Iss. 3, pp. 687-701
Closed Access | Times Cited: 43
The study of coal gangue segmentation for location and shape predicts based on multispectral and improved Mask R-CNN
Wenhao Lai, Feng Hu, Xixi Kong, et al.
Powder Technology (2022) Vol. 407, pp. 117655-117655
Closed Access | Times Cited: 40
Detection of Coal and Gangue Based on Improved YOLOv8
Qingliang Zeng, Guangyu Zhou, Lirong Wan, et al.
Sensors (2024) Vol. 24, Iss. 4, pp. 1246-1246
Open Access | Times Cited: 16
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
Cascade network for detection of coal and gangue in the production context
Ziqi Lv, Weidong Wang, Zhiqiang Xu, et al.
Powder Technology (2020) Vol. 377, pp. 361-371
Closed Access | Times Cited: 58
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
Automatic Coal and Gangue Segmentation Using U-Net Based Fully Convolutional Networks
Rong Gao, Zhaoyun Sun, Wei Li, et al.
Energies (2020) Vol. 13, Iss. 4, pp. 829-829
Open Access | Times Cited: 51
Fine-grained object detection method using attention mechanism and its application in coal–gangue detection
Ziqi Lv, Weidong Wang, Zhiqiang Xu, et al.
Applied Soft Computing (2021) Vol. 113, pp. 107891-107891
Closed Access | Times Cited: 43
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
Coal and Gangue Separating Robot System Based on Computer Vision
Zhiyuan Sun, Linlin Huang, Ruiqing Jia
Sensors (2021) Vol. 21, Iss. 4, pp. 1349-1349
Open Access | Times Cited: 35
Fast recognition using convolutional neural network for the coal particle density range based on images captured under multiple light sources
Feiyan Bai, Minqiang Fan, Hongli Yang, et al.
International Journal of Mining Science and Technology (2021) Vol. 31, Iss. 6, pp. 1053-1061
Open Access | Times Cited: 30
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
A Swin transformer-functionalized lightweight YOLOv5s for real-time coal–gangue detection
Xiao Wen, Bo Li, Xuewen Wang, et al.
Journal of Real-Time Image Processing (2023) Vol. 20, Iss. 3
Closed Access | Times Cited: 11
LPT-Net: A Line-Pad Transformer Network for efficiency coal gangue segmentation with linear multi-head self-attention mechanism
Tao Ye, Hao Chen, Ren Hong-bin, et al.
Measurement (2024) Vol. 226, pp. 114043-114043
Closed Access | Times Cited: 4
Lightweight coal and gangue detection algorithm based on improved Yolov7-tiny
Zhenguan Cao, Zhuoqin Li, Liao Fang, et al.
International Journal of Coal Preparation and Utilization (2024) Vol. 44, Iss. 11, pp. 1773-1792
Closed Access | Times Cited: 4
Spatial Effect Analysis of Coal and Gangue Recognition Detector Based on Natural Gamma Ray Method
Mingxin Zhao, Huaishan Liu, Changyou Liu, et al.
Natural Resources Research (2022) Vol. 31, Iss. 2, pp. 953-969
Closed Access | Times Cited: 17
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
A Novel Deep Learning Model Based on YOLOv5 Optimal Method for Coal Gangue Image Recognition
Tongkai Gu, Haiyan Zhao, Yasheng Chang, et al.
Research Square (Research Square) (2025)
Closed Access
Recognition and sorting of coal and gangue based on image process and multilayer perceptron
Junhao Jiang, Yanfeng Han, Huijun Zhao, et al.
International Journal of Coal Preparation and Utilization (2021) Vol. 43, Iss. 1, pp. 54-72
Closed Access | Times Cited: 22
Using Deep Convolutional Neural Networks and Infrared Thermography to Identify Coal Quality and Gangue
Refat Mohammed Abdullah Eshaq, Eryi Hu, Hamzah A. A. M. Qaid, et al.
IEEE Access (2021) Vol. 9, pp. 147315-147327
Open Access | Times Cited: 21
YOLOv4-Tiny-Based Coal Gangue Image Recognition and FPGA Implementation
Shanyong Xu, ZHOU Yujie, Yourui Huang, et al.
Micromachines (2022) Vol. 13, Iss. 11, pp. 1983-1983
Open Access | Times Cited: 16
A Faster and Lighter Detection Method for Foreign Objects in Coal Mine Belt Conveyors
Bingxin Luo, Ziming Kou, Cong Han, et al.
Sensors (2023) Vol. 23, Iss. 14, pp. 6276-6276
Open Access | Times Cited: 8
A review of deep leaning in image classification for mineral exploration
Yang Liu, Xueyi Wang, Zelin Zhang, et al.
Minerals Engineering (2023) Vol. 204, pp. 108433-108433
Closed Access | Times Cited: 8
Intelligent Gangue Sorting System Based on Dual-Energy X-ray and Improved YOLOv5 Algorithm
Yuchen Qin, Ziming Kou, Cong Han, et al.
Applied Sciences (2023) Vol. 14, Iss. 1, pp. 98-98
Open Access | Times Cited: 7
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