Detecting Out-Of-Distribution Labels in Image Datasets With Pre-trained Networks

Ensuring the correctness of annotations in training datasets is one way to increase the trustworthiness and reli- ability of Machine Learning. This study aims to detect semantic shifts in datasets using Feature-Based Out-Of- Distribution and outlier detection