19 citations · 21 across the 5 of their papers we have counts for
5 papers
DailyMAE: Towards Pretraining Masked Autoencoders in One Day
Jiantao Wu, Shentong Mo, Sara Atito +3
Recently, masked image modeling (MIM), an important self-supervised learning (SSL) method, has drawn attention for its effectiveness in learning data representation from unlabeled…
LT-ViT: A Vision Transformer for multi-label Chest X-ray classification
Umar Marikkar, Sara Atito, Muhammad Awais +1
Vision Transformers (ViTs) are widely adopted in medical imaging tasks, and some existing efforts have been directed towards vision-language training for Chest X-rays (CXRs). Howev…
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition
Cong Wu, Xiao-Jun Wu, Josef Kittler +4
Contrastive learning has achieved great success in skeleton-based action recognition. However, most existing approaches encode the skeleton sequences as entangled spatiotemporal re…
Masked Momentum Contrastive Learning for Zero-shot Semantic Understanding
Jiantao Wu, Shentong Mo, Muhammad Awais +3
Self-supervised pretraining (SSP) has emerged as a popular technique in machine learning, enabling the extraction of meaningful feature representations without labelled data. In th…
SB-SSL: Slice-Based Self-Supervised Transformers for Knee Abnormality Classification from MRI
Sara Atito, Syed Muhammad Anwar, Muhammad Awais +1
The availability of large scale data with high quality ground truth labels is a challenge when developing supervised machine learning solutions for healthcare domain. Although, the…