15 citations · 32 across the 7 of their papers we have counts for
7 papers
AutoFraudNet: A Multimodal Network to Detect Fraud in the Auto Insurance Industry
Azin Asgarian, Rohit Saha, Daniel Jakubovitz +1
In the insurance industry detecting fraudulent claims is a critical task with a significant financial impact. A common strategy to identify fraudulent claims is looking for inconsi…
GaLeNet: Multimodal Learning for Disaster Prediction, Management and Relief
Rohit Saha, Mengyi Fang, Angeline Yasodhara +7
After a natural disaster, such as a hurricane, millions are left in need of emergency assistance. To allocate resources optimally, human planners need to accurately analyze data th…
On the Trustworthiness of Tree Ensemble Explainability Methods
Angeline Yasodhara, Azin Asgarian, Diego Huang +1
The recent increase in the deployment of machine learning models in critical domains such as healthcare, criminal justice, and finance has highlighted the need for trustworthy meth…
Prediction of Workplace Injuries
Mehdi Sadeqi, Azin Asgarian, Ariel Sibilia
Workplace injuries result in substantial human and financial losses. As reported by the International Labour Organization (ILO), there are more than 374 million work-related injuri…
Limitations and Biases in Facial Landmark Detection -- An Empirical Study on Older Adults with Dementia
Azin Asgarian, Shun Zhao, Ahmed B. Ashraf +5
Accurate facial expression analysis is an essential step in various clinical applications that involve physical and mental health assessments of older adults (e.g. diagnosis of pai…
A Hybrid Instance-based Transfer Learning Method
Azin Asgarian, Parinaz Sobhani, Ji Chao Zhang +4
In recent years, supervised machine learning models have demonstrated tremendous success in a variety of application domains. Despite the promising results, these successful models…
Subspace Selection to Suppress Confounding Source Domain Information in AAM Transfer Learning
Azin Asgarian, Ahmed Bilal Ashraf, David Fleet +1
Active appearance models (AAMs) are a class of generative models that have seen tremendous success in face analysis. However, model learning depends on the availability of detailed…