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TAI-SARNET: Deep Transferred Atrous-Inception CNN for Small Samples SAR ATR
2020
Sensors
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To solve the problem, an effective lightweight Convolutional Neural Network (CNN) model incorporating transfer learning is proposed for better handling SAR targets recognition tasks. ...
improving the model's recognition performance on small sample SAR target datasets. ...
[45] propose a method for classification of small samples based on deep CNN. ...
doi:10.3390/s20061724
pmid:32204506
pmcid:PMC7146637
fatcat:zgag5vn4l5abvjktxuplcnxpei
SAR Target Recognition via Meta-Learning and Amortized Variational Inference
2020
Sensors
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The challenge of small data has emerged in synthetic aperture radar automatic target recognition (SAR-ATR) problems. ...
Most SAR-ATR methods are data-driven and require a lot of training data that are expensive to collect. ...
The model was also compared with deep transferred atrous-inception synthetic aperture radar network (TAI-SARNET), TAI-SARNET with transfer learning (TAI-SARNET-TF), and MobileNet. ...
doi:10.3390/s20205966
pmid:33096933
fatcat:clkcauglbfeurnvnblxnkzfuni