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1 Ergebnisse
1
Video-SwinUNet: Spatio-temporal Deep Learning Framework for..:
, In:
2023 IEEE International Conference on Image Processing (ICIP)
,
Zeng, Chengxi
;
Yang, Xinyu
;
Smithard, David
... - p. 2470-2474 , 2023
Link:
https://doi.org/10.1109/ICIP49359.2023.10222212
RT T1 <cTitle>2023 IEEE International Conference on Image Processing (ICIP)</cTitle>: T1 <Title>Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10222212&Exemplar=1&LAN=DE A1 Zeng, Chengxi A1 Yang, Xinyu A1 Smithard, David A1 Mirmehdi, Majid A1 Gambaruto, Alberto M A1 Burghardt, Tilo YR 2023 K1 Deep learning K1 Image segmentation K1 Neural networks K1 Semantics K1 Pipelines K1 Performance gain K1 Feature extraction K1 Deep Learning K1 Swin Transformer K1 Video Tracking K1 Dysphagia K1 Videofluoroscopy SP 2470 OP 2474 LK http://dx.doi.org/https://doi.org/10.1109/ICIP49359.2023.10222212 DO https://doi.org/10.1109/ICIP49359.2023.10222212 SF ELIB - SuUB Bremen
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