An efficient reconfigurable hardware accelerator for convolutional neural networks - researchr publication authors

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Anaam Ansari, Kiran Gunnam, Tokunbo Ogunfunmi. An efficient reconfigurable hardware accelerator for convolutional neural networks. In Michael B. Matthews, editor, 51st Asilomar Conference on Signals, Systems, and Computers, ACSSC 2017, Pacific Grove, CA, USA, October 29 - November 1, 2017. pages 1337-1341, IEEE, 2017. [doi]

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