Results 1 to 10 of about 377 (160)

Research on Recognition of Coal and Gangue Based on Laser Speckle Images [PDF]

open access: yesSensors, 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
doaj   +6 more sources

A Study of Multispectral Technology and Two-Dimension Autoencoder for Coal and Gangue Recognition [PDF]

open access: yesIEEE Access, 2020
Coal is one of the main sources of human energy. In the process of coal mining, separating gangue from coal has great significance for environmental protection and energy conservation.
Wenhao Lai   +4 more
doaj   +4 more sources

Coal/Gangue Recognition Using Convolutional Neural Networks and Thermal Images [PDF]

open access: yesIEEE 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
doaj   +4 more sources

Coal gangue detection and recognition algorithm based on deformable convolution YOLOv3 [PDF]

open access: yesIET 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
doaj   +3 more sources

Image Recognition of Coal and Coal Gangue Using a Convolutional Neural Network and Transfer Learning [PDF]

open access: yesEnergies, 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
doaj   +4 more sources

Study on recognition of coal and gangue based on multimode feature and image fusion

open access: yesPLoS ONE, 2023
Aiming at the problems of low accuracy of coal gangue recognition and difficult recognition of mixed gangue rate, a coal rock recognition method based on modal fusion of RGB and infrared is proposed. A fully mechanized coal gangue transportation test bed
Lijuan Zhao   +6 more
doaj   +4 more sources

Coal gangue recognition based on spectral imaging combined with XGBoost.

open access: yesPLoS 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
doaj   +4 more sources

Multi-Strategy Improvement of Coal Gangue Recognition Method of YOLOv11. [PDF]

open access: yesSensors (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.
europepmc   +4 more sources

X-ray transmission intelligent coal-gangue recognition method

open access: yesGong-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
doaj   +2 more sources

YOLOv4-Tiny-Based Coal Gangue Image Recognition and FPGA Implementation

open access: yesMicromachines, 2022
Nowadays, most of the deep learning coal gangue identification methods need to be performed on high-performance CPU or GPU hardware devices, which are inconvenient to use in complex underground coal mine environments due to their high power consumption, huge size, and significant heat generation.
Xu Shanyong
exaly   +4 more sources

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