1 code implementation • 28 Nov 2022 • Lalithkumar Seenivasan, Mobarakol Islam, Mengya Xu, Chwee Ming Lim, Hongliang Ren
Conclusion: The proposed multi-task model was able to adapt to domain shifts, incorporate novel instruments in the target domain, and perform tool-tissue interaction detection and report generation on par with single-task models.
1 code implementation • 10 Dec 2021 • Mobarakol Islam, Vibashan VS, Chwee Ming Lim, Hongliang Ren
We generate the task-aware saliency maps and scanpath of the instruments on the dataset of the MICCAI 2017 robotic instrument segmentation challenge.
1 code implementation • 23 Jul 2021 • Mengya Xu, Mobarakol Islam, Chwee Ming Lim, Hongliang Ren
To adapt incremental classes and extract domain invariant features, a class-incremental (CI) learning method with supervised contrastive (SupCon) loss is incorporated with a feature extractor.