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Differentiable Multi-Fidelity Fusion: Efficient Learning of Physics Simulations with Neural Architecture Search and Transfer Learning
With rapid progress in deep learning, neural networks have been widely used in scientific research and engineering applications as surrogate models.
SAR-ShipNet: SAR-Ship Detection Neural Network via Bidirectional Coordinate Attention and Multi-resolution Feature Fusion
This paper studies a practically meaningful ship detection problem from synthetic aperture radar (SAR) images by the neural network.
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