# BCNN: A Binary CNN with All Matrix Ops Quantized to 1 Bit Precision

Source: [BCNN: A Binary CNN with All Matrix Ops Quantized to 1 Bit Precision](<https://www.sota2.com/research/paper/68fa696d1e209131cea21f0f>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T22:59:51.007Z

Authors: Arthur J. Redfern, Lijun Zhu, Molly K. Newquist

Published: 2020-10-01T22:04:13.000Z

## Abstract

This paper describes a CNN where all CNN style 2D convolution operations that lower to matrix matrix multiplication are fully binary. The network is derived from a common building block structure that is consistent with a constructive proof outline showing that binary neural networks are universal function approximators. 71.24% top 1 accuracy on the 2012 ImageNet validation set was achieved with a 2 step training procedure and implementation strategies optimized for binary operands are provided.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2010.00704>)

[PDF](<https://arxiv.org/pdf/2010.00704.pdf>)