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Running Deep Neural Network (DNN) models on devices with limited computational capability is a challenge due to large compute and memory requirements.
High performance convolutional neural networks for document processing. In Tenth International Workshop on Frontiers in Handwriting Recognition
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Binarized Neural Networks. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain
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Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC. In Field-Programmable Technology (FPT), 2016 International Conference on
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gemmlowp: a small self-contained low-precision GEMM library
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FINN: A Framework for Fast, Scalable Binarized Neural Network Inference. In Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays
Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Leong, Magnus Jahre, and Kees Vissers. 2017 · 2017
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