FQ-Conv: Fully Quantized Convolution for Efficient and Accurate Inference

19 Dec 2019Bram-Ernst VerhoefNathan LaubeufStefan CosemansPeter DebackerIoannis PapistasArindam MallikDiederik Verkest

Deep neural networks (DNNs) can be made hardware-efficient by reducing the numerical precision of the weights and activations of the network and by improving the network's resilience to noise. However, this gain in efficiency often comes at the cost of significantly reduced accuracy... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper