Optimized network for detecting burr breakage in Milling Workpieces Images

Network architecture

Accuracy

Sensitivity

Performance metrics (time and trainable parameters)

URL to publisher version:

https://academic.oup.com/jigpal/article-abstract/32/4/624/7632101?redirectedFrom=fulltext

Cite as:

@article{66b88cea110bef475d852aa0,

title={Optimized network for detecting burr-breakage in images of milling workpieces}, 

volume={32}, 

ISSN={1368-9894}, 

DOI={10.1093/JIGPAL/JZAE024}, 

number={4}, 

journal={Logic Journal of the IGPL}, 

publisher={Oxford University Press}, 

author={Del Castillo, Virginia Riego and Sánchez-González, Lidia and Strisciuglio, Nicola}, 

year={2024}, 

pages={624-633}, 

keywords={burrs in workpiece ; CNN explanation ; computational performance ; convolutional neural network ; milling machined parts ; Quality estimation} 

}