2024
Retaining Informative Latent Variables in Probabilistic Segmentation
M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud van Sloun, Peter H. N. de With, Fons van der Sommen
ICASSP 2024accepted
Conditional latent-variable models can successfully quantify annotation variability in segmentation. Training such models involves tuning the dimensionality of the latent space to optimally capture the inherent data ambiguity. Nevertheless, we discover after careful tuning, that the latent space doe…