4 papers · 1 filter
Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning
Jiawen Xu, Odej Kao
Open set recognition (OSR) and continual learning are two critical challenges in machine learning, focusing respectively on detecting novel classes at inference time and updating m…
Informed Mixing -- Improving Open Set Recognition via Attribution-based Augmentation
Jiawen Xu, Odej Kao, Margret Keuper
Open set recognition (OSR) is devised to address the problem of detecting novel classes during model inference. Even in recent vision models, this remains an open issue which is re…
Know Yourself Better: Diverse Object-Related Features Improve Open Set Recognition
Jiawen Xu, Margret Keuper
Open set recognition (OSR) is a critical aspect of machine learning, addressing the challenge of detecting novel classes during inference. Within the realm of deep learning, neural…
OpenIncrement: A Unified Framework for Open Set Recognition and Deep Class-Incremental Learning
Jiawen Xu, Claas Grohnfeldt, Odej Kao
In most works on deep incremental learning research, it is assumed that novel samples are pre-identified for neural network retraining. However, practical deep classifiers often mi…