6 papers · 1 filter
iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data
Al Zadid Sultan Bin Habib, Md Younus Ahamed, Prashnna Gyawali +2
Multimodal learning of images and tabular data is often impaired by ineffective representations, resulting in redundancy, dispersion, and generalization problems. To tackle this ch…
Naming the Concepts Classifiers Rely On: Language-Anchored Decomposition for Faithful Explanation
Ahsan Habib Akash, Dipkamal Bhusal, Stacey Jones +3
Deep neural networks are widely deployed in high-stakes visual applications where interpretability is critical, yet existing explanations face a trade-off: post-hoc concept methods…
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…
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…
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…
Z-GMOT: Zero-shot Generic Multiple Object Tracking
Kim Hoang Tran, Anh Duy Le Dinh, Tien Phat Nguyen +6
Despite recent significant progress, Multi-Object Tracking (MOT) faces limitations such as reliance on prior knowledge and predefined categories and struggles with unseen objects.…