Improvement of Bagging performance for classification of imbalanced datasets using evolutionary multi-objective optimization. - Seyed Ehsan Roshan; Shahrokh Asadi (Eng. Appl. Artif. Intell., 2020)

Random forest swarm optimization-based for heart diseases diagnosis. - Shahrokh Asadi; Seyed Ehsan Roshan; Michael W. Kattan (J. Biomed. Informatics, 2021)

A bi-objective optimization method to produce a near-optimal number of classifiers and increase diversity in Bagging. - Shahrokh Asadi; Seyed Ehsan Roshan (Knowl. Based Syst., 2021)

Development of ensemble learning classification with density peak decomposition-based evolutionary multi-objective optimization. - Seyed Ehsan Roshan; Shahrokh Asadi (Int. J. Mach. Learn. Cybern., 2021)

IMBoost: A New Weighting Factor for Boosting to Improve the Classification Performance of Imbalanced Data. - Seyed Ehsan Roshan; Jafar Tanha; Farzad Hallaji; Mohammadreza Ghanbari (Complex., 2023)

A deep ensemble medical image segmentation with novel sampling method and loss function. - Seyed Ehsan Roshan; Jafar Tanha; Mahdi Zarrin; Alireza Fakhim Babaei; Haniyeh Nikkhah; Zahra Jafari (Comput. Biol. Medicine, 2024)

A Novel Multimodal Deep Learning Approach With Loss Function for Detection of Sleep Apnea Events. - Alireza Fakhim Babaei; Jafar Tanha; Mohammad Ali Balafar; Seyed Ehsan Roshan (IEEE Access, 2025)

YM-WML: A new Yolo-based segmentation Model with Weighted Multi-class Loss for medical imaging. - Haniyeh Nikkhah; Jafar Tanha; Mahdi Zarrin; Seyed Ehsan Roshan; Amin Kazempour (CoRR, 2025)