Author

A. Temi̇zel

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#machine learning Preprint Oct 2026

Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies

A framework in which a classifier, trained on normal images and on synthetic anomalies, scores a test image without comparing it with normal data is proposed, suggesting that clean benchmark scores can hide a strong sensitivity to capture conditions, and that learning the decision from both normal images and rule viola...

Ufuk Efe, A. Temi̇zel · 0 citations

Review Open access 2026

Explainable Sensitive Content Moderation With Vocabulary-Aware Distillation

The Sensitive Benchmark (SenBen), a large-scale scene graph dataset of 13,999 movie frames from 157 films, is introduced and a multi-task distillation recipe targeting vocabulary imbalance in autoregressive scene graph generation is proposed targeting vocabulary imbalance in autoregressive scene graph generation.

Fatih Cagatay Akyon, A. Temi̇zel · IEEE Access · 0 citations