Oct 26, 2023 · This approach enhances feature extraction and representation ability for few-shot SAR targets. Additionally, an adaptive hyper-parameter update ...
Oct 19, 2023 · In synthetic aperture radar automatic target recognition (SAR-ATR), the limitations of imaging environment and observation conditions make ...
The code in this toolbox implements the "Few-Shot SAR Target Recognition Through Meta-Adaptive Hyperparameters Learning for Fast Adaptation" in IEEE ...
Few-Shot SAR Target Recognition Through Meta-Adaptive Hyperparameters' Learning for Fast Adaptation. IEEE Trans. Geosci. Remote. Sens. 61: 1-17 (2023); 2022.
After training, MSAR can implement fast adaptation with a few training images on new tasks. To the best of our knowledge, this is the first study to solve a few ...
Oct 31, 2020 · The experimental results validate that the Adaptive Learning of hyperparameters for Fast Adaptation ... few-shot learning approaches.
Missing: SAR Target
This work proposes a novel few-shot learning (FSL) method for SAR image recognition, which is composed of the multi-feature fusion network (MFFN) and the ...
[PDF] Meta-Learning with Adaptive Hyperparameters - NIPS papers
proceedings.neurips.cc › paper › file
With the proposed training scheme ALFA, fast adaptation to each task from even a random initial- ization shows a better few-shot classification accuracy than ...
Missing: SAR | Show results with:SAR
A cross time-domain sample transfer learning model based on the TrAdaBoost algorithm was used for the Cu content mapping in the topsoil by selective use of ...
In this study, we propose Meta-FSEO, a novel model for improving the performance of few-shot remote sensing scene classification in varying urban scenes. The ...