Journal ArticleDOI
Multi-information online detection of coal quality based on machine vision
TLDR
An exploratory study employing a bench-scale approach to detect the multi-information of coal quality online by machine vision simultaneously, including particle size distribution, density distribution, the ash content of each density fraction, and the total ash content.About:
This article is published in Powder Technology.The article was published on 2020-09-01. It has received 35 citations till now. The article focuses on the topics: Machine vision.read more
Citations
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Journal ArticleDOI
Ore image classification based on small deep learning model: Evaluation and optimization of model depth, model structure and data size
TL;DR: This paper attempts to explore a more suitable small deep learning model for ore image classification by considering the model depth, model structure, and dataset size.
Journal ArticleDOI
Deep learning-based damage detection of mining conveyor belt
TL;DR: The EfficientNet was adopted as the backbone feature extraction network instead of Darknet53 in the improved Yolov3 algorithm, which comprehensively considers the balance between network depth, width, and image resolution for network scaling to improve the accuracy of the algorithm in limited computing resources.
Journal ArticleDOI
Deep learning-based image classification for online multi-coal and multi-class sorting
TL;DR: This study builds four CNNs models with different depth and structure for multi-coal and multi-class image classification based on VGG Net, Inception Net, and Res Net and proposes a universal CNNs model suitable forMulti- coal andMulti-class sorting.
Journal ArticleDOI
Research into balance of rocks and underground cavities formation in the coal mine flowsheet when mining thin seams
TL;DR: The results of the work have been obtained within the framework of the research-and-development work "Development of advanced technologies for the complete mining of steam coal with the accumulation of waste rocks in the underground space".
Journal ArticleDOI
Deep Learning Based Mineral Image Classification Combined With Visual Attention Mechanism
TL;DR: In this paper, four visual attention blocks are designed and embedded in the existing CNNs model, and new mineral image classification models based on the visual attention mechanism and CNNs are proposed.
References
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Journal ArticleDOI
Online monitoring and control of froth flotation systems with machine vision: A review
TL;DR: Machine vision has been used to extract froth characteristics, both physical (e.g. bubble size) and dynamic (froth velocity) from digital images and present these results to operators and/or use the results as inputs to process control systems.
Journal ArticleDOI
A machine vision approach to on-line estimation of run-of-mine ore composition on conveyor belts
TL;DR: In this paper, a general machine vision approach for on-line estimation of rock mixture composition is described, and is illustrated on a very challenging nickel mineral system: very heterogeneous minerals, similar coloration, and rock fragments can be dry or wet.
Journal ArticleDOI
ESVM: evolutionary support vector machine for automatic feature selection and classification of microarray data.
Hui-Ling Huang,Fang-Lin Chang +1 more
TL;DR: An evolutionary approach to designing an SVM-based classifier (named ESVM) is proposed by simultaneous optimization of automatic feature selection and parameter tuning using an intelligent genetic algorithm, combined with k-fold cross-validation regarded as an estimator of generalization ability.
Journal ArticleDOI
Ore grade estimation by feature selection and voting using boundary detection in digital image analysis
Claudio A. Perez,Pablo A. Estevez,Pablo A. Vera,Luis E. Castillo,Carlos M. Aravena,Daniel A. Schulz,Leonel E. Medina +6 more
TL;DR: This paper presents a new method to improve rock classification using digital image analysis, feature selection based on mutual information and a voting process to take into account boundary information and shows that the RMSE on rock composition classification on a test database decreased 8.8% by using the proposed voting method with the automatic segmentation with respect to direct sub-image classification.
Journal ArticleDOI
Estimation of particle size distribution on an industrial conveyor belt using image analysis and neural networks
TL;DR: In this article, the size distribution of particles in a crushing circuit of a copper concentrator was estimated using image processing and neural network techniques, and the proposed soft sensors can be used for real time measurement of particle size distribution in the industrial operations instead of sophisticated and expensive instruments.
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