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1 Ergebnisse
1
Zero-Shot Performance of the Segment Anything Model (SAM) i..:
, In:
2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE)
,
Mattjie, Christian
;
De Moura, Luis Vinicius
;
Ravazio, Rafaela
... - p. 108-112 , 2023
Link:
https://doi.org/10.1109/BIBE60311.2023.00025
RT T1 <cTitle>2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE)</cTitle>: T1 <Title>Zero-Shot Performance of the Segment Anything Model (SAM) in 2D Medical Imaging: A Comprehensive Evaluation and Practical Guidelines</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10431886&Exemplar=1&LAN=DE A1 Mattjie, Christian A1 De Moura, Luis Vinicius A1 Ravazio, Rafaela A1 Kupssinsku, Lucas A1 Parraga, Otavio A1 Delucis, Marcelo Mussi A1 Barros, Rodrigo C. YR 2023 SN 2471-7819 K1 Image segmentation K1 Adaptation models K1 Ultrasonic imaging K1 Zero-shot learning K1 Biological system modeling K1 Biomedical imaging K1 Guidelines K1 Medical Imaging K1 Segmentation K1 Segment Anything Model K1 Zero-shot Learning K1 Deep Learning SP 108 OP 112 LK http://dx.doi.org/https://doi.org/10.1109/BIBE60311.2023.00025 DO https://doi.org/10.1109/BIBE60311.2023.00025 SF ELIB - SuUB Bremen
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