Coal gangue recognition based on spectral imaging combined with XGBoost. [PDF]
PLoS ONE, 2023 The identification of coal gangue is of great significance for its intelligent separation. To overcome the interference of visible light, we propose coal gangue recognition based on multispectral imaging and Extreme Gradient Boosting (XGBoost).
Minghao Zhou, Wenhao Lai
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Research on Recognition of Coal and Gangue Based on Laser Speckle Images [PDF]
Sensors, 2023 Coal gangue image recognition is a critical technology for achieving automatic separation in coal processing, characterized by its rapid, environmentally friendly, and energy-saving nature.
Hequn Li +5 more
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A multi modal fusion coal gangue recognition method based on IBWO-CNN-LSTM [PDF]
Scientific ReportsAccurate identification of coal and gangue is a crucial guarantee for efficient and safe mining of top coal caving face. This article proposes a coal-gangue recognition method based on an improved beluga whale optimization algorithm (IBWO), convolutional
Wenchao Hao +4 more
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X-ray transmission intelligent coal-gangue recognition method
Gong-kuang zidonghua, 2022 The coal-gangue image recognition is an important part of coal-gangue separation technology based on pseudo dual energy X-ray transmission (XRT). However, it is difficult to segment the coal-gangue image due to the close proximity or occlusion of coal ...
WANG Wenxin +4 more
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Coal-gangue recognition via multi-branch convolutional neural network based on MFCC in noisy environment [PDF]
Scientific Reports, 2023 Traditional coal-gangue recognition methods usually do not consider the impact of equipment noise, which severely limits its adaptability and recognition accuracy.
HaiYan Jiang +6 more
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Coal/Gangue Recognition Using Convolutional Neural Networks and Thermal Images [PDF]
IEEE Access, 2020 Recognition and separation of Coal/Gangue are important phases in the coal industries for many aspects. This paper addressed the topic of Coal/Gangue recognition and built a new model called (CGR-CNN) based on Convolutional Neural network (CNN) and using
Murad Saleh Alfarzaeai +4 more
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Multi-Strategy Improvement of Coal Gangue Recognition Method of YOLOv11. [PDF]
Sensors (Basel)The current methods for detecting coal gangue face several challenges, including low detection accuracy, a high probability of missed detections, and inadequate real-time performance. These issues stem from the complexities associated with diverse industrial environments and mining conditions, such as the mixing of coal gangue and insufficient ...
Tao H, Zhang L, Sun Z, Cui X, Yi W.
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Coal gangue detection and recognition algorithm based on deformable convolution YOLOv3 [PDF]
IET Image Processing, 2022 The intelligentisation of coal mines is the only approach to the high‐quality development of the coal industry. Detection, identification and sorting of coal gangue is an important part of the intelligentisation of coal mines.
De‐yong Li +3 more
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Image Recognition of Coal and Coal Gangue Using a Convolutional Neural Network and Transfer Learning [PDF]
Energies, 2019 Recognizing and distinguishing coal and gangue are essential in engineering, such as in coal-fired power plants. This paper employed a convolutional neural network (CNN) to recognize coal and gangue images and help segregate coal and gangue.
Yuanyuan Pu +3 more
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Research on efficient matching method of coal gangue recognition image and sorting image. [PDF]
Sci RepAbstract The coal gangue sorting robot may encounter variations in the pose of the target coal gangue due to belt slippage, deviation, and speed fluctuations, leading to failed or missed grasping attempts during the sorting process of coal gangue.
Ye Z +5 more
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