FAAGC augments scarce training data by fitting and sampling a per-class geodesic arc in the pre-shape space, producing modest accuracy gains over prior feature-augmentation baselines.
Feature-level smote: Augmenting fault samples in learnable feature space for imbal- anced fault diagnosis of gas turbines,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
FAAGC: Feature Augmentation on Adaptive Geodesic Curve Based on the shape space theory
FAAGC augments scarce training data by fitting and sampling a per-class geodesic arc in the pre-shape space, producing modest accuracy gains over prior feature-augmentation baselines.