Cuepervision: self-supervised learning for continuous domain adaptation without catastrophic forgetting-Reference-Cited by-同舟云学术

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Cuepervision: self-supervised learning for continuous domain adaptation without catastrophic forgetting

Published:2021-02 Issue: Volume:106 Page:104079
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Schutera Mark,Hafner Frank M.,Abhau Jochen,Hagenmeyer Veit,Mikut Ralf,Reischl Markus

Funder

Bundesministerium für Wirtschaft und Energie

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing

Reference39 articles.

1. Representation learning: a review and new perspectives;Bengio,2013

2. Adapting to Continuously Shifting Domains;Bobu,2018

3. Domain separation networks;Bousmalis,2016

4. Deep clustering for unsupervised learning of visual features;Caron,2018

5. Superposition of many models into one;Cheung,2019

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