Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Instanssegmentering"'
Autor:
Möller, Oliver
In the intricate domain of Printed Circuit Boards (PCBs), object detection poses unique challenges, particularly given the broad size spectrum of components, ranging from a mere 2 pixels to several thousand pixels within a single high-resolution imag
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-342952
Autor:
Russom, Simon Tsehaie
Quality inspection is an essential part of almost any industrial production line. However, designing customized solutions for defect detection for every product can be costlyfor the production line. This is especially the case for short-series produc
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-194881
Video instance segmentation is a rapidly-growing research area within the computer vision field. Models for segmentation require data already annotated, which can be a daunting task when starting from scratch. Although there are some publicly availab
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306040
Autor:
Norrman, Marcus, Shihab, Saad
This thesis investigates the performance of Mask R-CNN when utilizing transfer learning on a small dataset. The aim was to instance segment eyeglass lenses as accurately as possible from self-portrait images. Five different models were trained, where
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306909
Autor:
Sievert, Rolf
Instance segmentation has a great potential for improving the current state of littering by autonomously detecting and segmenting different categories of litter. With this information, litter could, for example, be geotagged to aid litter pickers or
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175173
Autor:
Norrman, Marcus, Shihab, Saad
This thesis investigates the performance of Mask R-CNN when utilizing transfer learning on a small dataset. The aim was to instance segment eyeglass lenses as accurately as possible from self-portrait images. Five different models were trained, where
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::79ea10dd28136e6c53389002908dad19
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306909
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306909
Autor:
Sievert, Rolf
Instance segmentation has a great potential for improving the current state of littering by autonomously detecting and segmenting different categories of litter. With this information, litter could, for example, be geotagged to aid litter pickers or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::dc65e6c188519c2bfc057ecaa0f03ef0
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175173
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175173