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Found 3 papers, 2 papers with code
Gradient-Regularized Out-of-Distribution Detection
In this work, we propose the idea of leveraging the information embedded in the gradient of the loss function during training to enable the network to not only learn a desired OOD score for each sample but also to exhibit similar behavior in a local neighborhood around each sample.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Entropic Open-set Active Learning
Active Learning (AL) aims to enhance the performance of deep models by selecting the most informative samples for annotation from a pool of unlabeled data.
Open-Set Automatic Target Recognition
Automatic Target Recognition (ATR) is a category of computer vision algorithms which attempts to recognize targets on data obtained from different sensors.
