2 papers
cs.LG2025
Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains
Hisashi Oshima, Tsuyoshi Ishizone, Tomoyuki Higuchi
Recent developments in the unsupervised domain adaptation (UDA) enable the unsupervised machine learning (ML) prediction for target data, thus this will accelerate real world appli…
cs.CV2024
Aortic root landmark localization with optimal transport loss for heatmap regression
Tsuyoshi Ishizone, Masaki Miyasaka, Sae Ochi +2
Anatomical landmark localization is gaining attention to ease the burden on physicians. Focusing on aortic root landmark localization, the three hinge points of the aortic valve ca…