most citedRethinking Self-Supervised Learning Within the Framework of Partial Information Decomposition

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.LG2024

GUESS: Generative Uncertainty Ensemble for Self Supervision

Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh

Self-supervised learning (SSL) frameworks consist of pretext task, and loss function aiming to learn useful general features from unlabeled data. The basic idea of most SSL baselin…

cs.CV20241 cited

Rethinking Self-Supervised Learning Within the Framework of Partial Information Decomposition

Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh

Self Supervised learning (SSL) has demonstrated its effectiveness in feature learning from unlabeled data. Regarding this success, there have been some arguments on the role that m…

cs.CV2024

Direct Coloring for Self-Supervised Enhanced Feature Decoupling

Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh

The success of self-supervised learning (SSL) has been the focus of multiple recent theoretical and empirical studies, including the role of data augmentation (in feature decouplin…

cs.CV2024

FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation

Trong Thang Pham, Ngoc-Vuong Ho, Nhat-Tan Bui +8

Developing an interpretable system for generating reports in chest X-ray (CXR) analysis is becoming increasingly crucial in Computer-aided Diagnosis (CAD) systems, enabling radiolo…

eess.IV2024

Efficient Classification of Histopathology Images

Mohammad Iqbal Nouyed, Mary-Anne Hartley, Gianfranco Doretto +1

This work addresses how to efficiently classify challenging histopathology images, such as gigapixel whole-slide images for cancer diagnostics with image-level annotation. We use i…