Detection of coal gangue by YOLO deep learning method based on channel pruning
IF 2
4区 工程技术
Q4 ENERGY & FUELS
International Journal of Coal Preparation and Utilization
Pub Date : 2024-03-23
DOI:10.1080/19392699.2024.2331545
引用次数: 0
Abstract
Rapid and accurate identification of coal and gangue is of great significance to improve sorting efficiency and reduce environmental pollution. Image recognition based on deep learning is the curre...基于通道剪枝的 YOLO 深度学习方法检测煤矸石
快速准确地识别煤炭和矸石对提高分拣效率、减少环境污染具有重要意义。基于深度学习的图像识别是目前最有效的分拣方法。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
求助全文
约1分钟内获得全文
求助全文
来源期刊
CiteScore
4.10
自引率
23.80%
发文量
106
审稿时长
6 months
期刊介绍：
International Journal of Coal Preparation and Utilization publishes original research papers, short communications, review articles, book reviews, and symposium announcements covering all aspects of coal preparation. The journal is significant reading for all individuals involved with coal preparation, including those in operations, engineering, management, education, and scientific research.
Topics include:
coal properties and coal petrography;
coal quality and characterization;
surface chemistry of coal and minerals;
crushing, grinding and liberation;
coal screening and classification;
dense medium and density separations;
froth flotation and oil agglomeration;
process control and optimization;
flocculation and thickening;
dewatering and thermal drying;
briquetting and pelletizing;
coal handling and storage;
coal utilization and blending;
waste disposal and pollution;
utility waste product utilization;
and carbon based material.
Additional subjects covered by the journal include properties of coal/water and coal/oil slurries as well as the processing of oil shales and tarsands by physical and physiochemical methods.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
