Eintrag in der Universitätsbibliographie der TU Chemnitz
Beuth, Frederik ; Schlosser, Tobias ; Friedrich, Michael ; Kowerko, Danny*
Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning
| Universität: | Technische Universität Chemnitz | |
| Förderung: | BMBF | |
| Institut: | Juniorprofessur Media Computing | |
| Dokumentart: | Preprint | |
| URL/URN: | http://arxiv.org/abs/2102.06955 | |
| Quelle: | This work is an extended arXiv version of the original conference article published in "IECON 2020": this https URL . The work has been extended regarding visual attention | |
| Freie Schlagwörter (Englisch): | Convolutional Neural Networks , Computer Vision , Fault Inspection , Semiconductor Manufacturing , Wafer Dicing |
