most citedAdaptiveSAM: Towards Efficient Tuning of SAM for Surgical Scene Segmentation

2 citations · 5 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

2 papers · 1 filter

cs.CV2023★ 2 cited

AdaptiveSAM: Towards Efficient Tuning of SAM for Surgical Scene Segmentation

Jay N. Paranjape, Nithin Gopalakrishnan Nair, Shameema Sikder +2

Segmentation is a fundamental problem in surgical scene analysis using artificial intelligence. However, the inherent data scarcity in this domain makes it challenging to adapt tra…

cs.CV2023★ 2 cited

GLSFormer: Gated - Long, Short Sequence Transformer for Step Recognition in Surgical Videos

Nisarg A. Shah, Shameema Sikder, S. Swaroop Vedula +1

Automated surgical step recognition is an important task that can significantly improve patient safety and decision-making during surgeries. Existing state-of-the-art methods for s…