From fde509a9a830d890eab6c7b6c73d48ce942cf56b Mon Sep 17 00:00:00 2001 From: daquexian Date: Tue, 8 Oct 2019 15:45:08 +0800 Subject: [PATCH 1/2] Update README about related works using dabnn --- README.md | 8 ++++++++ README_CN.md | 9 +++++++++ 2 files changed, 17 insertions(+) diff --git a/README.md b/README.md index d776440..4802f0b 100644 --- a/README.md +++ b/README.md @@ -80,6 +80,14 @@ For more details please read [our ACM MM paper](https://arxiv.org/abs/1908.05858 Android app demo: https://github.com/JDAI-CV/dabnn-example +## Related works using dabnn + +The following two papers use dabnn to measure the latency of their binary networks on real devices: + +[IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788) + +[Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117) + ## License and Citation [BSD 3 Clause](LICENSE) diff --git a/README_CN.md b/README_CN.md index b90bbc6..236f113 100644 --- a/README_CN.md +++ b/README_CN.md @@ -82,6 +82,15 @@ dabnn_bireal18_imagenet_stem 43294019 ns 41401923 ns 14 <--- 带 Android app demo: https://github.com/JDAI-CV/dabnn-example +## 使用了 dabnn 的相关工作 + +这两篇二值网络方向的相关工作引用了 dabnn 并使用 dabnn 测试二值网络在真实设备上的速度： + +[IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788) + +[Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117) + + ## 开源许可和引用 [BSD 3 Clause](LICENSE) From f1db5182e75c5ac775da503236d565c6c8b03a87 Mon Sep 17 00:00:00 2001 From: daquexian Date: Tue, 8 Oct 2019 15:46:41 +0800 Subject: [PATCH 2/2] Add * --- README.md | 4 ++-- README_CN.md | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 4802f0b..9ee5e78 100644 --- a/README.md +++ b/README.md @@ -84,9 +84,9 @@ Android app demo: https://github.com/JDAI-CV/dabnn-example The following two papers use dabnn to measure the latency of their binary networks on real devices: -[IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788) +* [IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788) -[Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117) +* [Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117) ## License and Citation diff --git a/README_CN.md b/README_CN.md index 236f113..12e163b 100644 --- a/README_CN.md +++ b/README_CN.md @@ -86,9 +86,9 @@ Android app demo: https://github.com/JDAI-CV/dabnn-example 这两篇二值网络方向的相关工作引用了 dabnn 并使用 dabnn 测试二值网络在真实设备上的速度： -[IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788) +* [IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788) -[Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117) +* [Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117) ## 开源许可和引用