A lightweight feature extraction backbone for gangue detection with improved Resnet50
IF 2
4区 工程技术
Q4 ENERGY & FUELS
International Journal of Coal Preparation and Utilization
Pub Date : 2024-08-22
DOI:10.1080/19392699.2024.2393885
引用次数: 0
Abstract
In response to the sizable parameters and floating point operations (FLOPs) of feature extraction backbone of gangue detection algorithm, a lightweight backbone was proposed by improving Resnet50. ...用于煤矸石检测的轻量级特征提取骨干网50
针对煤矸石检测算法中特征提取骨干网的参数和浮点运算（FLOPs）较大的问题，通过改进 Resnet50，提出了一种轻量级骨干网。...
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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.
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