research
∙
08/08/2023
Data Augmentation-Based Unsupervised Domain Adaptation In Medical Imaging
Deep learning-based models in medical imaging often struggle to generali...
share
research
∙
01/23/2023
Deep Learning-Based Assessment of Cerebral Microbleeds in COVID-19
Cerebral Microbleeds (CMBs), typically captured as hypointensities from ...
research
∙
08/30/2022
FAST-AID Brain: Fast and Accurate Segmentation Tool using Artificial Intelligence Developed for Brain
Medical images used in clinical practice are heterogeneous and not the s...
research
∙
04/21/2022
Learning spatiotemporal features from incomplete data for traffic flow prediction using hybrid deep neural networks
Urban traffic flow prediction using data-driven models can play an impor...
research
∙
12/22/2019
On the Initialization of Long Short-Term Memory Networks
Weight initialization is important for faster convergence and stability ...
research
∙
08/14/2019
Robust parametric modeling of Alzheimer's disease progression
Quantitative characterization of disease progression using longitudinal ...
research
∙
03/17/2019
Training recurrent neural networks robust to incomplete data: application to Alzheimer's disease progression modeling
Disease progression modeling (DPM) using longitudinal data is a challeng...
research
∙
08/16/2018
Robust training of recurrent neural networks to handle missing data for disease progression modeling
Disease progression modeling (DPM) using longitudinal data is a challeng...
research
∙
10/19/2017
Combining Multiple Views for Visual Speech Recognition
Visual speech recognition is a challenging research problem with a parti...
research
∙
10/19/2017
Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem GMM-HMM System
Automatic visual speech recognition is an interesting problem in pattern...
research
∙
06/09/2016