The ore image classification technology based on deep learning is an effective way to
improve the image sensor-based ore sorting classification capability. However, in practice …

Efficient sorting and optimal utilization have become the common core issues for today's
mining industry. Vision-based sorting technology provides a powerful answer to this …

Deep learning is an effective way to improve the classification accuracy of coal images for
the machine vision-based coal sorting. However, the related research on deep learning …

A nonlinear support vector machine (SVM) uses engineered features to classify the quality of
currently combusting coal as it is fired in an operating electric utility generator. The SVM …

Moisture is one of the important influencing factors on machine vision-based mineral image
classification, and it has different effects on various ore particles. At present, deep learning is …

Deep learning applications on computer vision involve the use of large-volume and
representative data to obtain state-of-the-art results due to the massive number of …

Combustion of pulverized coal involves millions of particles with a distribution of
morphologies. A workflow is presented to characterize, classify, and model distributions of …

Identification of coal and gangue is one of the important problems in the coal industry. To
improve the accuracy of coal gangue identification in the coal mining process, a coal …

For the classification of mixed particle with imaging method, the traditional processing
techniques tend to extract the particle features from binary images, where particles can be …

Coal is a primary natural resource of fuel that is efficiently used for electricity generation,
steel or iron production, and household usage. Characterization is needed for industries to …