A seq2seq model with a new adaptive-frequency layer learns the inverse mapping from flapping-wing forces to wing kinematics, improving median prediction error over transformer baselines by about 11% on two datasets.
Smart wing rotation and trailing-edge vortices enable high frequency mosquito flight
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A Deep Inverse-Mapping Model for a Flapping Robotic Wing
A seq2seq model with a new adaptive-frequency layer learns the inverse mapping from flapping-wing forces to wing kinematics, improving median prediction error over transformer baselines by about 11% on two datasets.