Computational intelligence and neuroscience
36193183
Automatic segmentation of coal crack in CT images is of great significance for the establishment of digital cores. In addition, segmentation in this field remains challenging due to some properties of coal crack CT images: high noise, small targets, ...
Computational intelligence and neuroscience
35785104
In the complex underground environment, the paths planned for coal mine patrol robot are often too long and unsmooth under the influence of low visibility and poor road conditions. To solve the problems, this paper improves the hybrid algorithm betwe...
Environmental science and pollution research international
35488989
The major emission sources of NO are from automobiles, trucks, and various non-road vehicles, power plants, coal fired boilers, cement kilns, turbines, etc. Plasma reactor technology is widely used in gas conversion applications, such as NOx conversi...
Coal burst prediction is an important research hotspot in coal mine production safety. This paper presents FDNet, which is a knowledge and data fusion-driven deep neural network for coal burst prediction. The main idea of FDNet is to extract explicit...
Real-time coal mine intelligent monitoring for pedestrian identifying and positioning is an important means to ensure safety in production. Traditional object detection models based on neural networks require significant computational and storage res...
PURPOSE: This paper aims to develop a successful deep learning model with data augmentation technique to discover the clinical uniqueness of chest X-ray imaging features of coal workers' pneumoconiosis (CWP).
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
36356397
Proximate analysis of coal is of profound significance for understanding coal quality and promoting rational utilization of coal resources. Traditional coal proximate analysis mainly uses chemical analysis methods, which have the disadvantages of slo...
International journal of environmental research and public health
36232168
Coal and gas outbursts seriously threaten the mining safety of deep coal mines. The evaluation of the risk grade of these events can effectively prevent the occurrence of safety accidents in deep coal mines. Characterized as a high-dimensional, nonli...
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...
Coal production often involves a substantial presence of gangue and foreign matter, which not only impacts the thermal properties of coal and but also leads to damage to transportation equipment. Selection robots for gangue removal have garnered atte...