Deep neural networks require large training sets but suffer from high computational cost and
long training times. Training on much smaller training sets while maintaining nearly the …

Our paper focuses on the topic of unsupervised domain adaptation for person re-
identification (UDA re-ID) in an end-to-end framework. Currently, most existing methods …

To improve the recognition rate of lower limb actions based on surface electromyography
(sEMG), an effective weighted feature method is proposed, and an improved genetic …

Hardware Trojan detection method has been given particular attentions by hardware
security researchers since the failure of Syrian radars in 2007. Electromagnetic side-channel …

This brief presents a novel spatio-temporal domain adaptation (DA) method that is
unsupervised and event-driven for dynamic vision sensor (DVS) gesture recognition. This …

Adaptation of a classifier to new domains is one of the challenging problems in machine
learning. This has been addressed using many deep and non-deep learning based …

The goal of Zero-shot Learning (ZSL) is to discriminate images from unseen classes by
modelling the embedding relationship between visual and semantic features. However …

Unsupervised domain adaptation (UDA) tries to utilize the labeled source domain
knowledge to help the learning of unlabeled target domain. Existing methods address this …