3 citations · 5 across the 3 of their papers we have counts for
5 papers
CDA: Contrastive-adversarial Domain Adaptation
Nishant Yadav, Mahbubul Alam, Ahmed Farahat +3
Recent advances in domain adaptation reveal that adversarial learning on deep neural networks can learn domain invariant features to reduce the shift between source and target doma…
Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data with Spatial Information
Lasitha Vidyaratne, Mahbubul Alam, Alexander Glandon +3
Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extra…
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz +5
Deep learning classifiers are assisting humans in making decisions and hence the user's trust in these models is of paramount importance. Trust is often a function of constant beha…
Survey on Deep Neural Networks in Speech and Vision Systems
Mahbubul Alam, Manar D. Samad, Lasitha Vidyaratne +2
This survey presents a review of state-of-the-art deep neural network architectures, algorithms, and systems in vision and speech applications. Recent advances in deep artificial n…
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritum…