GANsemble for Small and Imbalanced Data Sets: A Baseline for Synthetic Microplastics Data

arXiv:2404.07356v1 Announce Type: new
Abstract: Microplastic particle ingestion or inhalation by humans is a problem of growing concern. Unfortunately, current research methods that use machine learning to understand their potential harms are obstructed by a lack of available data. Deep learning techniques in particular are challenged by such domains where only small or imbalanced data sets are available. Overcoming this challenge often involves oversampling underrepresented classes or augmenting the existing data to improve model performance. This paper proposes GANsemble: a …

abstract arxiv cs.ai cs.cv cs.lg current data data sets deep learning deep learning techniques humans machine machine learning particle research small synthetic type