Abstract

This thesis is about finding wrongly labeled data in datasets. Errors were injected in the MNIST and CIFAR10 datasets on two error levels. The hypothesis is that it is possible to find wrongly labeled data through studying the loss function on individual losses. The result shows that it is possible.