2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 2 cited
Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging
Jielin Qiu, Peide Huang, Makiya Nakashima +10
Self-supervised learning is crucial for clinical imaging applications, given the lack of explicit labels in healthcare. However, conventional approaches that rely on precise vision…
eess.IV2022
Interaction of a priori Anatomic Knowledge with Self-Supervised Contrastive Learning in Cardiac Magnetic Resonance Imaging
Makiya Nakashima, Inyeop Jang, Ramesh Basnet +6
Training deep learning models on cardiac magnetic resonance imaging (CMR) can be a challenge due to the small amount of expert generated labels and inherent complexity of data sour…
cs.LG2019
An Ensemble Approach toward Automated Variable Selection for Network Anomaly Detection
Makiya Nakashima, Alex Sim, Youngsoo Kim +2
While variable selection is essential to optimize the learning complexity by prioritizing features, automating the selection process is preferred since it requires laborious effort…