ADCG: A Cross-Modality Domain Transfer Learning Method for Synthetic Aperture Radar in Ship Automatic Target Recognition

Author:

Gao Gui1ORCID,Dai Yuxi1,Zhang Xi2ORCID,Duan Dingfeng1ORCID,Guo Fei3

Affiliation:

1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China

2. Laboratory of Marine Physics and Remote Sensing, First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China

3. Shanghai Institute of Satellite Engineering, Shanghai, China

Funder

National Nature Science Foundation of China

Innovation Team of the Ministry of Education of China

Innovation Group of Sichuan Natural Science Foundation

Fundamental Research Funds for the Central Universities

CAST Innovation Foundation

State Key Laboratory of Geo-Information Engineering

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Reference45 articles.

1. Transfer Learning with Deep Convolutional Neural Network for SAR Target Classification with Limited Labeled Data

2. Artificial generation of big data for improving image classification: A generative adversarial network approach on SAR data;marmanis;Proc IEEE Conf Comput Vis Pattern Recognit,2017

3. EfficientNet: Rethinking model scaling for convolutional neural networks;tan;Proc IEEE Conf Comput Vis Pattern Recognit,2019

4. Identifying Corresponding Patches in SAR and Optical Images With a Pseudo-Siamese CNN

5. Combining a single shot multibox detector with transfer learning for ship detection using sentinel-1 SAR images

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