Survey of unknown object detection with Barcina-Blanco
Survey of unknown object detection with Barcina-Blanco
Managing the unknown: a survey on Open Set Recognition and tangential areas
arXiv paper abstract https://arxiv.org/abs/2312.08785
arXiv PDF paper https://arxiv.org/pdf/2312.08785.pdf
In real-world scenarios classification models are often required to perform robustly when predicting samples belonging to classes that have not appeared during its training stage.
Open Set Recognition addresses this issue by devising models capable of detecting unknown classes from samples arriving during the testing phase, while maintaining a good level of performance in the classification of samples belonging to known classes.
This review comprehensively overviews the recent literature related to Open Set Recognition, identifying common practices, limitations, and connections of this field with other machine learning research areas, such as continual learning, out-of-distribution detection, novelty detection, and uncertainty estimation.
... work also uncovers open problems and suggests several research directions that may motivate and articulate future efforts towards more safe Artificial Intelligence methods.
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