activity
20172023
most citedGenerative Probabilistic Novelty Detection with Adversarial Autoencoders

136 citations · 148 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CL2023★ 1 cited

Cardiovascular Disease Risk Prediction via Social Media

Al Zadid Sultan Bin Habib, Md Asif Bin Syed, Md Tanvirul Islam +1

Researchers use Twitter and sentiment analysis to predict Cardiovascular Disease (CVD) risk. We developed a new dictionary of CVD-related keywords by analyzing emotions expressed i…

cs.CV2022★ 2 cited

Learning Representations for Masked Facial Recovery

Zaigham Randhawa, Shivang Patel, Donald Adjeroh +1

The pandemic of these very recent years has led to a dramatic increase in people wearing protective masks in public venues. This poses obvious challenges to the pervasive use of fa…

cs.CV2022

FUSSL: Fuzzy Uncertain Self Supervised Learning

Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh

Self supervised learning (SSL) has become a very successful technique to harness the power of unlabeled data, with no annotation effort. A number of developed approaches are evolvi…

cs.CV2022

Deep Active Ensemble Sampling For Image Classification

Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh

Conventional active learning (AL) frameworks aim to reduce the cost of data annotation by actively requesting the labeling for the most informative data points. However, introducin…

eess.SP2022★ 3 cited

Multimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised Learning

Thinh Phan, Duc Le, Patel Brijesh +4

Electrocardiogram (ECG) signal is one of the most effective sources of information mainly employed for the diagnosis and prediction of cardiovascular diseases (CVDs) connected with…

q-bio.GN2021

Human Age Estimation from Gene Expression Data using Artificial Neural Networks

Salman Mohamadi, Gianfranco. Doretto, Nasser M. Nasrabadi +1

The study of signatures of aging in terms of genomic biomarkers can be uniquely helpful in understanding the mechanisms of aging and developing models to accurately predict the age…