About the Equivalence Between Complex-Valued and Real-Valued Fully Connected Neural Networks - Application to Polinsar Images-Reference-Cited by-同舟云学术

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About the Equivalence Between Complex-Valued and Real-Valued Fully Connected Neural Networks - Application to Polinsar Images

Published:2021-10-25 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)
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Author:

Barrachina J. A.,Ren C.,Vieillard G.,Morisseau C.,Ovarlez J.-P.

Funder

Délégation Générale de 1’ Armement (DGA)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9596063/9596068/09596542.pdf?arnumber=9596542

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CVNN-Based Microwave Imaging Approach;2023 IEEE Conference on Antenna Measurements and Applications (CAMA);2023-11-15

2. PolSAR Image Classification Using Attention Based Shallow to Deep Convolutional Neural Network;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16

3. Impact of PolSAR Pre-Processing and Balancing Methods on Complex-Valued Neural Networks Segmentation Tasks;IEEE Open Journal of Signal Processing;2023

4. Real- and Complex-Valued Neural Networks for SAR Image Segmentation Through Different Polarimetric Representations;2022 IEEE International Conference on Image Processing (ICIP);2022-10-16

5. Comparison Between Equivalent Architectures of Complex-valued and Real-valued Neural Networks - Application on Polarimetric SAR Image Segmentation;Journal of Signal Processing Systems;2022-07-28

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