3 papers
cs.CV2025
Learning to Harmonize Cross-vendor X-ray Images by Non-linear Image Dynamics Correction
Yucheng Lu, Shunxin Wang, Dovile Juodelyte +1
In this paper, we explore how conventional image enhancement can improve model robustness in medical image analysis. By applying commonly used normalization methods to images from…
cs.CV2025
Do ImageNet-trained models learn shortcuts? The impact of frequency shortcuts on generalization
Shunxin Wang, Raymond Veldhuis, Nicola Strisciuglio
Frequency shortcuts refer to specific frequency patterns that models heavily rely on for correct classification. Previous studies have shown that models trained on small image data…
cs.CV2025
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
Boqian Wu, Qiao Xiao, Shunxin Wang +5
It is generally perceived that Dynamic Sparse Training opens the door to a new era of scalability and efficiency for artificial neural networks at, perhaps, some costs in accuracy…