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In-Sensor Radio Frequency Computing for Energy-Efficient Intelligent Radar
Radio Frequency Neural Networks (RFNNs) have demonstrated advantages in realizing intelligent applications across various domains.
Algorithm and Hardware Co-Design of Energy-Efficient LSTM Networks for Video Recognition with Hierarchical Tucker Tensor Decomposition
Meanwhile, compared with the state-of-the-art tensor decomposed model-oriented hardware TIE, our proposed FDHT-LSTM architecture achieves better performance in throughput, area efficiency and energy efficiency, respectively on LSTM-Youtube workload.
Robot Motion Planning as Video Prediction: A Spatio-Temporal Neural Network-based Motion Planner
Despite the current development in this direction, the efficient capture and processing of important sequential and spatial information, in a direct and simultaneous way, is still relatively under-explored.
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