1) Deep Neural Network-Based Radar Signal Processing for Real-Time Applications (2019): This paper provides an overview of the various deep neural networks that can be used to process radar signals in real-time. It provides descriptions of the various architectures and their performance in a variety of scenarios. This paper is highly recommended for those interested in the application of deep neural networks for signal processing in real-time. Rating: 8/10

2) Real-Time Detection of Moving Targets Using Deep Learning on Radar Signals (2018): This paper presents a deep learning-based approach to detect moving targets in real-time using radar signals. It describes the architecture of the proposed system, as well as its evaluation in a variety of scenarios. This paper is a good overview of the potential of deep learning in radar signal processing, and is recommended for those interested in this field. Rating: 7/10

3) Multi-Sensor Radar System Fusion Using Deep Learning (2016): This paper presents a deep learning-based approach to multi-sensor radar system fusion. It describes the architecture of the proposed system, as well as its evaluation in a variety of scenarios. This paper is an interesting overview of the potential of deep learning in radar signal fusion, and is recommended for those interested in applying deep learning to multi-sensor radar systems. Rating: 6/10
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