3 papers
cs.CV2026
A Systematic Comparison of Training Objectives for Out-of-Distribution Detection in Image Classification
Furkan Genç, Furkan Genç, Onat Ãzdemir +3
Out-of-distribution (OOD) detection is critical in safety-sensitive applications. While this challenge has been addressed from various perspectives, the influence of training objec…
cs.CV2026
MatchED: Crisp Edge Detection Using End-to-End, Matching-based Supervision
Bedrettin Cetinkaya, Sinan Kalkan, Emre Akbas
Generating crisp, i.e., one-pixel-wide, edge maps remains one of the fundamental challenges in edge detection, affecting both traditional and learning-based methods. To obtain cris…
cs.LG2025
Class Uncertainty: A Measure to Mitigate Class Imbalance
Z. S. Baltaci, K. Oksuz, S. Kuzucu +5
Class-wise characteristics of training examples affect the performance of deep classifiers. A well-studied example is when the number of training examples of classes follows a long…