Searched for: subject%3A%22Global%255C%2BInterpretability%22
(1 - 1 of 1)
SOILIS, Panagiotis (author)
Deep learning models have achieved state-of-the-art performance on several image classification tasks over the past years. Several studies claim to approach or even surpass human-levels of performance when using such models to classify images. However, these architectures are notoriously complex, thus making their interpretation a challenge....
master thesis 2020