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20222024
most citedAccurate, Low-latency, Efficient SAR Automatic Target Recognition on FPGA

21 citations · 27 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.DC2024

Accelerating ViT Inference on FPGA through Static and Dynamic Pruning

Dhruv Parikh, Shouyi Li, Bingyi Zhang +3

Vision Transformers (ViTs) have achieved state-of-the-art accuracy on various computer vision tasks. However, their high computational complexity prevents them from being applied t…

cs.DC2024

GCV-Turbo: End-to-end Acceleration of GNN-based Computer Vision Tasks on FPGA

Bingyi Zhang, Rajgopal Kannan, Carl Busart +1

Graph neural networks (GNNs) have recently empowered various novel computer vision (CV) tasks. In GNN-based CV tasks, a combination of CNN layers and GNN layers or only GNN layers…

cs.CV2024

VTR: An Optimized Vision Transformer for SAR ATR Acceleration on FPGA

Sachini Wickramasinghe, Dhruv Parikh, Bingyi Zhang +3

Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) is a key technique used in military applications like remote-sensing image recognition. Vision Transformers (ViTs)…

cs.CV2024

Uncertainty-Aware SAR ATR: Defending Against Adversarial Attacks via Bayesian Neural Networks

Tian Ye, Rajgopal Kannan, Viktor Prasanna +1

Adversarial attacks have demonstrated the vulnerability of Machine Learning (ML) image classifiers in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems. An…

cs.CV2024

PAHD: Perception-Action based Human Decision Making using Explainable Graph Neural Networks on SAR Images

Sasindu Wijeratne, Bingyi Zhang, Rajgopal Kannan +2

Synthetic Aperture Radar (SAR) images are commonly utilized in military applications for automatic target recognition (ATR). Machine learning (ML) methods, such as Convolutional Ne…