Elena Camuffo — accepted AI-conference papers

2024

Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics

Elena Camuffo, Umberto Michieli, Simone Milani, Jijoong Moon, Mete Ozay

IROS 2024poster

Developing a reliable vision system is a fundamental challenge for robotic technologies (e.g., indoor service robots and outdoor autonomous robots) which can ensure reliable navigation even in challenging environments such as adverse weather conditions (e.g., fog, rain), poor lighting conditions (e.…

Cited by 1 Source ↗Scholar ↗

2024

FFT-Based Selection and Optimization of Statistics for Robust Recognition of Severely Corrupted Images

Elena Camuffo, Umberto Michieli, Jijoong Moon, Daehyun Kim, Mete Ozay

ICASSP 2024accepted

Improving model robustness in case of corrupted images is among the key challenges to enable robust vision systems on smart devices, such as robotic agents. Particularly, robust test-time performance is imperative for most of the applications. This paper presents a novel approach to improve robustne…

Cited by 0 Source ↗Scholar ↗