Weilong Peng

Generating Out-of-Distribution Examples via Feature Crossover against Overconfidence Issue

2023

The problem of overconfident predictions on out-of-distribution (OOD) samples poses a significant challenge to the reliability and robustness of deep neural networks (DNNs). The reason for OOD overconfidence issue is that DNNs only learn the …