jangsoopark/AConvNet-pytorch
PyTorch implementation of Target Classification Using the Deep Convolutional Networks for SAR Images
This project helps defense analysts and remote sensing specialists automatically identify targets in Synthetic Aperture Radar (SAR) images. You input raw SAR image data, including magnitude and phase blocks, and it outputs the classified target type (e.g., specific vehicle models). This is for professionals who need to quickly and accurately categorize objects detected by SAR systems.
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Use this if you need a robust and efficient way to classify ground targets from SAR imagery, particularly for the MSTAR dataset.
Not ideal if your primary need is processing optical imagery or other radar types, or if you require real-time classification on embedded systems with very limited computational resources.
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Dec 27, 2022
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