Encoding features robust to unseen modes of variation with attentive long short-term memory-Reference-Cited by-同舟云学术

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Encoding features robust to unseen modes of variation with attentive long short-term memory

Published:2020-04 Issue: Volume:100 Page:107159
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Baddar Wissam J.,Ro Yong Man

Funder

Institute for Information & communications Technology

Planning & Evaluation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference55 articles.

1. Disentangling the modes of variation in unlabelled data;Wang;IEEE Trans. Pattern Anal. Mach. Intell.,2017

2. NTU RGB+ D: a large scale dataset for 3D human activity analysis;Shahroudy,2016

3. View adaptive recurrent neural networks for high performance human action recognition from skeleton data;Zhang,2017

4. Robust face recognition via multimodal deep face representation;Ding;IEEE Trans. Multimed.,2015

5. Learning features robust to image variations with siamese networks for facial expression recognition;Baddar,2017

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1. Deep Graph neural network-based spammer detection under the perspective of heterogeneous cyberspace;Future Generation Computer Systems;2021-04

2. Efficient and effective training of sparse recurrent neural networks;Neural Computing and Applications;2021-01-26

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