Transfer knowledge across different feature domains and build classifiers above the transferred knowledges.
Transfer Neural Trees is proposed to transfer classifiers to a different dimensional space with deep neural network.
Information of labeled source-domain data is transferred to the unlabeled target-domain, which may be a small set with imbalanced label counts.
Closest Common Space Learning is proposed to combine sub-domain level classifiers to identify better source data applicability.
A set of labeled source-domain data is used to construct classifier for the unlabeled target-domain data.
An algorithm is proposed to address source-target mismatch and project them to a common space.
Review papers as external reviewer for IEEE ICCV, IEEE ECCV, IEEE AAAI, and IEEE IJCAI.
Remove noises in PPG signals induced by motions by decorrelating the PPG with accelerometer signal.
An algorithm is proposed to project the signal into a complex plane, in which a temporal filter will be performed, followed by ensemble voting for the optimal beat counts.
Compress the data perceived by a sensor array using less data storage than what it used to consume.
Establish a time-continuous model of human neurons to simulate the biological effects at stimulus and message passing.
Build deep models for cuisine images using TensorFlow on multi-GPU machines, providing a backend with an API.
Offer tutoring for high school physics, competition physics, GRE subject test (physics), and SAT II subject test (physics).
Two students became national representatives for Taiwan in International Physics Olympiad (IPhO).