3 papers
cs.LG2025
Sampling and Loss Weights in Multi-Domain Training
Mahdi Salmani, Pratik Worah, Meisam Razaviyayn +1
In the training of large deep neural networks, there is a need for vast amounts of training data. To meet this need, data is collected from multiple domains, such as Wikipedia and…
cs.CV2025
From Filters to VLMs: Benchmarking Defogging Methods through Object Detection and Segmentation Performance
Ardalan Aryashad, Parsa Razmara, Amin Mahjoub +3
Autonomous driving perception systems are particularly vulnerable in foggy conditions, where light scattering reduces contrast and obscures fine details critical for safe operation…
cs.LG2025
Rewriting the Budget: A General Framework for Black-Box Attacks Under Cost Asymmetry
Mahdi Salmani, Alireza Abdollahpoorrostam, Seyed-Mohsen Moosavi-Dezfooli
Traditional decision-based black-box adversarial attacks on image classifiers aim to generate adversarial examples by slightly modifying input images while keeping the number of qu…