6 citations · 6 across the 1 of their papers we have counts for
5 papers
Automated femur segmentation from computed tomography images using a deep neural network
P. A. Bjornsson, B. Helgason, H. Palsson +3
Osteoporosis is a common bone disease that occurs when the creation of new bone does not keep up with the loss of old bone, resulting in increased fracture risk. Adults over the ag…
Deep-Learning-Based Audio-Visual Speech Enhancement in Presence of Lombard Effect
Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson +1
When speaking in presence of background noise, humans reflexively change their way of speaking in order to improve the intelligibility of their speech. This reflex is known as Lomb…
Unsupervised brain lesion segmentation from MRI using a convolutional autoencoder
Hans E. Atlason, Askell Love, Sigurdur Sigurdsson +2
Lesions that appear hyperintense in both Fluid Attenuated Inversion Recovery (FLAIR) and T2-weighted magnetic resonance images (MRIs) of the human brain are common in the brains of…
Effects of Lombard Reflex on the Performance of Deep-Learning-Based Audio-Visual Speech Enhancement Systems
Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson +1
Humans tend to change their way of speaking when they are immersed in a noisy environment, a reflex known as Lombard effect. Current speech enhancement systems based on deep learni…
On Training Targets and Objective Functions for Deep-Learning-Based Audio-Visual Speech Enhancement
Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson +1
Audio-visual speech enhancement (AV-SE) is the task of improving speech quality and intelligibility in a noisy environment using audio and visual information from a talker. Recentl…