CN110110852A - 一种深度学习网络移植到fpag平台的方法 - Google Patents
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- CN110110852A CN110110852A CN201910400926.2A CN201910400926A CN110110852A CN 110110852 A CN110110852 A CN 110110852A CN 201910400926 A CN201910400926 A CN 201910400926A CN 110110852 A CN110110852 A CN 110110852A
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110738241A (zh) * | 2019-09-24 | 2020-01-31 | 中山大学 | 一种基于神经网络的双目立体视觉匹配方法及其运算框架 |
CN111783974A (zh) * | 2020-08-12 | 2020-10-16 | 成都佳华物链云科技有限公司 | 模型构建及图像处理方法、装置、硬件平台及存储介质 |
CN112699384A (zh) * | 2020-12-11 | 2021-04-23 | 山东大学 | 基于fpga的全同态加密深度学习推理方法及系统 |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP6183980B1 (ja) * | 2016-12-02 | 2017-08-23 | 国立大学法人東京工業大学 | ニューラルネットワーク回路装置、ニューラルネットワーク、ニューラルネットワーク処理方法およびニューラルネットワークの実行プログラム |
US20180046903A1 (en) * | 2016-08-12 | 2018-02-15 | DeePhi Technology Co., Ltd. | Deep processing unit (dpu) for implementing an artificial neural network (ann) |
US20180046894A1 (en) * | 2016-08-12 | 2018-02-15 | DeePhi Technology Co., Ltd. | Method for optimizing an artificial neural network (ann) |
WO2018140294A1 (en) * | 2017-01-25 | 2018-08-02 | Microsoft Technology Licensing, Llc | Neural network based on fixed-point operations |
CN108416318A (zh) * | 2018-03-22 | 2018-08-17 | 电子科技大学 | 基于数据增强的合成孔径雷达图像目标深度模型识别方法 |
JP2018132830A (ja) * | 2017-02-13 | 2018-08-23 | LeapMind株式会社 | ニューラルネットワーク構築方法、ニューラルネットワーク装置及びニューラルネットワーク装置更新方法 |
WO2019059191A1 (ja) * | 2017-09-20 | 2019-03-28 | 国立大学法人東京工業大学 | ニューラルネットワーク回路装置、ニューラルネットワーク、ニューラルネットワーク処理方法およびニューラルネットワークの実行プログラム |
CN109657787A (zh) * | 2018-12-19 | 2019-04-19 | 电子科技大学 | 一种二值忆阻器的神经网络芯片 |
-
2019
- 2019-05-15 CN CN201910400926.2A patent/CN110110852B/zh active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20180046903A1 (en) * | 2016-08-12 | 2018-02-15 | DeePhi Technology Co., Ltd. | Deep processing unit (dpu) for implementing an artificial neural network (ann) |
US20180046894A1 (en) * | 2016-08-12 | 2018-02-15 | DeePhi Technology Co., Ltd. | Method for optimizing an artificial neural network (ann) |
JP6183980B1 (ja) * | 2016-12-02 | 2017-08-23 | 国立大学法人東京工業大学 | ニューラルネットワーク回路装置、ニューラルネットワーク、ニューラルネットワーク処理方法およびニューラルネットワークの実行プログラム |
WO2018140294A1 (en) * | 2017-01-25 | 2018-08-02 | Microsoft Technology Licensing, Llc | Neural network based on fixed-point operations |
JP2018132830A (ja) * | 2017-02-13 | 2018-08-23 | LeapMind株式会社 | ニューラルネットワーク構築方法、ニューラルネットワーク装置及びニューラルネットワーク装置更新方法 |
WO2019059191A1 (ja) * | 2017-09-20 | 2019-03-28 | 国立大学法人東京工業大学 | ニューラルネットワーク回路装置、ニューラルネットワーク、ニューラルネットワーク処理方法およびニューラルネットワークの実行プログラム |
CN108416318A (zh) * | 2018-03-22 | 2018-08-17 | 电子科技大学 | 基于数据增强的合成孔径雷达图像目标深度模型识别方法 |
CN109657787A (zh) * | 2018-12-19 | 2019-04-19 | 电子科技大学 | 一种二值忆阻器的神经网络芯片 |
Non-Patent Citations (3)
Title |
---|
HARUYOSHI YONEKAWA: ""On-chip memory based binarized convolutional deep neural network applying batch normalization free technique on an FPGA"" * |
仇越: ""基于FPGA的卷积神经网络加速方法研究及实现"" * |
李嘉辉;蔡述庭;陈学松;熊晓明;: "基于FPGA的卷积神经网络的实现" * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110738241A (zh) * | 2019-09-24 | 2020-01-31 | 中山大学 | 一种基于神经网络的双目立体视觉匹配方法及其运算框架 |
CN111783974A (zh) * | 2020-08-12 | 2020-10-16 | 成都佳华物链云科技有限公司 | 模型构建及图像处理方法、装置、硬件平台及存储介质 |
CN112699384A (zh) * | 2020-12-11 | 2021-04-23 | 山东大学 | 基于fpga的全同态加密深度学习推理方法及系统 |
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