26 citations · 87 across the 16 of their papers we have counts for
4 papers · 1 filter
DiffPAD: Denoising Diffusion-based Adversarial Patch Decontamination
Jia Fu, Xiao Zhang, Sepideh Pashami +2
In the ever-evolving adversarial machine learning landscape, developing effective defenses against patch attacks has become a critical challenge, necessitating reliable solutions t…
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis
Abdallah Alabdallah, Omar Hamed, Mattias Ohlsson +2
The Cox Proportional Hazards (CPH) model has long been the preferred survival model for its explainability. However, to increase its predictive power beyond its linear log-risk, it…
Artificial Intelligence Approaches for Predictive Maintenance in the Steel Industry: A Survey
Jakub Jakubowski, Natalia Wojak-Strzelecka, Rita P. Ribeiro +4
Predictive Maintenance (PdM) emerged as one of the pillars of Industry 4.0, and became crucial for enhancing operational efficiency, allowing to minimize downtime, extend lifespan…
Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks
Mohammed Ghaith Altarabichi, Sławomir Nowaczyk, Sepideh Pashami +2
This paper investigates how various randomization techniques impact Deep Neural Networks (DNNs). Randomization, like weight noise and dropout, aids in reducing overfitting and enha…