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08/08/2023
Data Augmentation-Based Unsupervised Domain Adaptation In Medical Imaging
Deep learning-based models in medical imaging often struggle to generali...
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01/23/2023
Deep Learning-Based Assessment of Cerebral Microbleeds in COVID-19
Cerebral Microbleeds (CMBs), typically captured as hypointensities from ...
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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...
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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...
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12/22/2019
On the Initialization of Long Short-Term Memory Networks
Weight initialization is important for faster convergence and stability ...
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08/14/2019
Robust parametric modeling of Alzheimer's disease progression
Quantitative characterization of disease progression using longitudinal ...
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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...
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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...
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10/19/2017
Combining Multiple Views for Visual Speech Recognition
Visual speech recognition is a challenging research problem with a parti...
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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...
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06/09/2016
