3 papers
cs.CV2022
Evaluating Uncertainty Calibration for Open-Set Recognition
Zongyao Lyu, Nolan B. Gutierrez, William J. Beksi
Despite achieving enormous success in predictive accuracy for visual classification problems, deep neural networks (DNNs) suffer from providing overconfident probabilities on out-o…
eess.IV2021
Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive Fields
Nolan B. Gutierrez, William J. Beksi
Thermal images model the long-infrared range of the electromagnetic spectrum and provide meaningful information even when there is no visible illumination. Yet, unlike imagery that…
cs.CV2021
An Uncertainty Estimation Framework for Probabilistic Object Detection
Zongyao Lyu, Nolan B. Gutierrez, William J. Beksi
In this paper, we introduce a new technique that combines two popular methods to estimate uncertainty in object detection. Quantifying uncertainty is critical in real-world robotic…