GPU-Accelerated Real-Time Stereo Estimation With Binary Neural Network

Depth estimation from stereo images is essential to many applications such as robotics and autonomous vehicles, most of which ask for the real-time response, high energy and storage efficiency. Recent work has shown deep neural networks (DNN) perform extremely well for stereo estimation. However, th...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems 2020-12, Vol.31 (12), p.2896-2907
Hauptverfasser:	Chen, Gang, Meng, Haitao, Liang, Yucheng, Huang, Kai
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximation Artificial neural networks binary neural network Computational modeling Convolution Energy storage Estimation Frames (data processing) Frames per second GPU acceleration Graphics processing units Mathematical analysis Neural networks Optimization Real time Real-time systems Robotics Similarity stereo estimation Time response
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