no code implementations • 1 Jul 2022 • Minh Cao, Ramin Ramezani
Recent advancements in computer graphics technology allow more realistic ren-dering of car driving environments.
no code implementations • 1 Jul 2022 • Minh Cao, Brett Bailey, WenHao Zhang, Solana Fernandez, Aaron Han, Smiti Narayanan, Shrineel Patel, Steven Saletta, Alexandra Stavrakis, Stephen Speicher, Stephanie Seidlits, Arash Naeim, Ramin Ramezani
It is to reduce hospital stay duration and overall medical cost after Total Knee Arthroplasty (TKA) procedures.
no code implementations • 28 Jun 2022 • Minh Cao, Tianqi Zhao, Yanxun Li, WenHao Zhang, Peyman Benharash, Ramin Ramezani
In this paper, we propose a deep transfer learning framework that is aimed to perform classification on a small size training dataset.
no code implementations • 10 May 2021 • WenHao Zhang, Ramin Ramezani, Arash Naeim
We will discuss causal inference and ways to discover the cause-effect from observational studies in healthcare domain.
no code implementations • 23 Oct 2019 • Vishwa Karia, Wen-Hao Zhang, Arash Naeim, Ramin Ramezani
In this paper, we present a novel technique based on genetic algorithms, GenSample, for oversampling the minority class in imbalanced datasets.
no code implementations • 17 Oct 2019 • Wenhao Zhang, Ramin Ramezani, Arash Naeim
In this paper, we propose a novel method that combines a Weighted Oversampling Technique and ensemble Boosting method (WOTBoost) to improve the classification accuracy of minority data without sacrificing the accuracy of the majority class.
no code implementations • 16 Oct 2019 • Wenhao Zhang, Wentian Bao, Xiao-Yang Liu, Keping Yang, Quan Lin, Hong Wen, Ramin Ramezani
In addition, our methods are based on the multi-task learning framework and mitigate the data sparsity issue.