reweighted-RNN: An Interpretable Recurrent Neural Network for Video Reconstruction via Deep Unfolding · Eutopia OER Connect

Title: reweighted-RNN: An Interpretable Recurrent Neural Network for Video Reconstruction via Deep Unfolding
Description: Code for our paper: "Designing Interpretable Recurrent Neural Networks for Video Reconstruction Via Deep Unfolding" Van Luong, H., Joukovsky, B., & Deligiannis, N. (2021). Designing Interpretable Recurrent Neural Networks for Video Reconstruction via Deep Unfolding. IEEE Transactions on Image Processing, 30, 4099-4113.
Creator: Boris Joukovsky Joukovsky
Contributor: Electronics and Informatics | Faculty of Engineering
Date: 13 Apr 2021
Identifier: https://hdl.handle.net/20.500.14017/f3e793ba-f2f6-4f73-ba21-487dc6adb9bc
Type: Software
Language: en
Source: https://researchportal.vub.be/en/publications/reweighted-rnn-an-interpretable-recurrent-neural-network-for-vide/
Relation: DOI: https://doi.org/10.5281/zenodo.4683941
Rights: Rights not stated in the record; consult the VUB Research Portal / rights holder
Educational Level: Higher education | research
Interactivity Type: Active