24 citations · 43 across the 4 of their papers we have counts for
4 papers · 1 filter
Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image Segmentation
Jamshid Hassanpour, Vinkle Srivastav, Didier Mutter +1
Self-supervised learning (SSL) approaches have achieved great success when the amount of labeled data is limited. Within SSL, models learn robust feature representations by solving…
Weakly Supervised Temporal Convolutional Networks for Fine-grained Surgical Activity Recognition
Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez +6
Automatic recognition of fine-grained surgical activities, called steps, is a challenging but crucial task for intelligent intra-operative computer assistance. The development of c…
Temporally Constrained Neural Networks (TCNN): A framework for semi-supervised video semantic segmentation
Deepak Alapatt, Pietro Mascagni, Armine Vardazaryan +7
A major obstacle to building models for effective semantic segmentation, and particularly video semantic segmentation, is a lack of large and well annotated datasets. This bottlene…
Single- and Multi-Task Architectures for Tool Presence Detection Challenge at M2CAI 2016
Andru P. Twinanda, Didier Mutter, Jacques Marescaux +2
The tool presence detection challenge at M2CAI 2016 consists of identifying the presence/absence of seven surgical tools in the images of cholecystectomy videos. Here, we propose t…