ProactiV : Studying Deep Learning Model Behavior Under Input Transformations

Deep learning (DL) models have shown performance benefits across many applications, from classification to image-to-image translation. However, low interpretability often leads to unexpected model behavior once deployed in the real world. Usually, this unexpected behavior is because the training dat...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 30(2024), 8 vom: 01. Juli, Seite 5651-5665
1. Verfasser: Prasad, Vidya (VerfasserIn)
Weitere Verfasser: van Sloun, Ruud J G, Vilanova, Anna, Pezzotti, Nicola
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article