3 papers
cs.LG2024
Confidence Calibration of Classifiers with Many Classes
Adrien LeCoz, Stéphane Herbin, Faouzi Adjed
For classification models based on neural networks, the maximum predicted class probability is often used as a confidence score. This score rarely predicts well the probability of…
cs.CV2024
Explaining an image classifier with a generative model conditioned by uncertainty
Adrien LeCoz, Stéphane Herbin, Faouzi Adjed
We propose to condition a generative model by a given image classifier uncertainty in order to analyze and explain its behavior. Preliminary experiments on synthetic data and a cor…
cs.CV2024
Leveraging generative models to characterize the failure conditions of image classifiers
Adrien LeCoz, Stéphane Herbin, Faouzi Adjed
We address in this work the question of identifying the failure conditions of a given image classifier. To do so, we exploit the capacity of producing controllable distributions of…