3 papers
cs.CV2025
A Contrastive Teacher-Student Framework for Novelty Detection under Style Shifts
Hossein Mirzaei, Mojtaba Nafez, Moein Madadi +12
There have been several efforts to improve Novelty Detection (ND) performance. However, ND methods often suffer significant performance drops under minor distribution shifts caused…
cs.LG2025
Scanning Trojaned Models Using Out-of-Distribution Samples
Hossein Mirzaei, Ali Ansari, Bahar Dibaei Nia +10
Scanning for trojan (backdoor) in deep neural networks is crucial due to their significant real-world applications. There has been an increasing focus on developing effective gener…
cs.CV2025
Mitigating Spurious Negative Pairs for Robust Industrial Anomaly Detection
Hossein Mirzaei, Mojtaba Nafez, Jafar Habibi +2
Despite significant progress in Anomaly Detection (AD), the robustness of existing detection methods against adversarial attacks remains a challenge, compromising their reliability…