3 citations · 7 across the 6 of their papers we have counts for
6 papers
Token-Based Detection of Spurious Correlations in Vision Transformers
Solha Kang, Esla Timothy Anzaku, Wesley De Neve +4
Due to their powerful feature association capabilities, neural network-based computer vision models have the ability to detect and exploit unintended patterns within the data, pote…
Towards Affordable Tumor Segmentation and Visualization for 3D Breast MRI Using SAM2
Solha Kang, Eugene Kim, Joris Vankerschaver +1
Breast MRI provides high-resolution volumetric imaging critical for tumor assessment and treatment planning, yet manual interpretation of 3D scans remains labor-intensive and subje…
Exploring Patient Data Requirements in Training Effective AI Models for MRI-based Breast Cancer Classification
Solha Kang, Wesley De Neve, Francois Rameau +1
The past decade has witnessed a substantial increase in the number of startups and companies offering AI-based solutions for clinical decision support in medical institutions. Howe…
Identifying Critical Tokens for Accurate Predictions in Transformer-based Medical Imaging Models
Solha Kang, Joris Vankerschaver, Utku Ozbulak
With the advancements in self-supervised learning (SSL), transformer-based computer vision models have recently demonstrated superior results compared to convolutional neural netwo…
Self-supervised Benchmark Lottery on ImageNet: Do Marginal Improvements Translate to Improvements on Similar Datasets?
Utku Ozbulak, Esla Timothy Anzaku, Solha Kang +2
Machine learning (ML) research strongly relies on benchmarks in order to determine the relative effectiveness of newly proposed models. Recently, a number of prominent research eff…
Utilizing Mutations to Evaluate Interpretability of Neural Networks on Genomic Data
Utku Ozbulak, Solha Kang, Jasper Zuallaert +2
Even though deep neural networks (DNNs) achieve state-of-the-art results for a number of problems involving genomic data, getting DNNs to explain their decision-making process has…