most citedTraining CNN Classifiers for Semantic Segmentation using Partially Annotated Images: with Application on Human Thigh and Calf MRI

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2025

Position as Probability: Self-Supervised Transformers that Think Past Their Training for Length Extrapolation

Philip Heejun Lee

Deep sequence models typically degrade in accuracy when test sequences significantly exceed their training lengths, yet many critical tasks--such as algorithmic reasoning, multi-st…

eess.IV2020★ 1 cited

Training CNN Classifiers for Semantic Segmentation using Partially Annotated Images: with Application on Human Thigh and Calf MRI

Chun Kit Wong, Stephanie Marchesseau, Maria Kalimeri +10

Objective: Medical image datasets with pixel-level labels tend to have a limited number of organ or tissue label classes annotated, even when the images have wide anatomical covera…