SAR Automatic Target Recognition Based on Multiview Deep Learning Framework

By Jifang Pei, Yulin Huang, Weibo Huo, Yin Zhang, Jianyu Yang, T. Yeo. IEEE Transactions on Geoscience and Remote Sensing, 2018

295 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Oceanography

View Paper: https://www.semanticscholar.org/paper/97a487be252e9f49614e2bd64f4ce7b2dbc1620a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Fang Liu
2. Lingling Li
3. Yiming Pi
4. L. Jiao
5. Rong Qu
6. Shuyuan Yang
7. Zhixi Feng
8. Zongyong Cui

Citations in the corpus

• A Survey of Deep Learning-Based Object Detection (2019, background): “[152] present a deep learning framework on synthetic aperture radar (SAR) automatic target”
• Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition (2020, methodology): “Most recent methods for ATR are based on supervised learning [1], [2].”