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Tzu-Chiang Tai

2 accepted papers

2023

Dense Adversarial Transfer Learning Based On Class-Invariance

ICASSP 2023accepted

This work proposes the dense adversarial transfer learning based on class-invariance, which is a novel, unsupervised, conditional adversarial domain adaptation approach. The proposed framework concatenates feature maps from the last layer of each backbone’s block to improve transfer learning; these…

Cited by 0SourceScholar
2018

Image Representation Using Supervised and Unsupervised Learning Methods on Complex Domain

ICASSP 2018accepted

Matrix factorization (MF) and its extensions have been intensively studied in computer vision and machine learning. In this paper, unsupervised and supervised learning methods based on MF technique on complex domain are introduced. Projective complex matrix factorization (PCMF) and discriminant proj…

Cited by 0SourceScholar