DgrCLR: Dual Gradient Reinforcement Contrastive Learning for Coal Gangue Classification
Author:
Affiliation:
1. School of Electronic Information Engineering, Foshan University,Foshan,China
2. School of Mechatronic Engineering and Automation, Foshan University,Foshan,China
3. Electronic Information school, Foshan polytechnic,Foshan,China
Funder
National Natural Science Foundation of China
Department of Science and Technology of Guangdong Province
Key Research and Development Program of Guangdong Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10488913/10488921/10489383.pdf?arnumber=10489383
Reference39 articles.
1. Nondestructive Identification of Coal and Gangue via Near-infrared Spectroscopy based on Improved Broad Learning
2. Experimental study on separation of lumpish coal and gangue using X-ray
3. Vibration Test of Single Coal Gangue Particle Directly Impacting the Metal Plate and the Study of Coal Gangue Recognition Based on Vibration Signal and Stacking Integration
4. Classification of coal and gangue under multiple surface conditions via machine vision and relief-SVM
5. Research on Coal Gangue Identification by Using Convolutional Neural Network
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