Work

A Computationally Efficient Density-Aware Adversarial Resampling Framework Using Wasserstein GANs for Imbalance and Overlapping Data Classification

Year: 2025

Type: article

Abstract: Effectively handling imbalanced datasets remains a fundamental challenge in computational modeling and machine learning, particularly when class overlap significantly deteriorates classification performance. Traditional overs... | Find, read and cite all the research you need on Tech Science Press

Source: Computer Modeling in Engineering & Sciences

DOI: 10.32604/cmes.2025.066514

Authors: Sidra Jubair, Jie Yang, Bilal Ali, Walid Emam, Yusra Tashkandy

Institutions: Central South University, Dalian University of Technology, King Saud University

Language: English

Topic: Imbalanced Data Classification Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: King Saud University

Award: G2461468828