CN112396178A - 一种提高cnn网络压缩效率的方法 - Google Patents
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CN107679617A (zh) * | 2016-08-22 | 2018-02-09 | 北京深鉴科技有限公司 | 多次迭代的深度神经网络压缩方法 |
US20180046894A1 (en) * | 2016-08-12 | 2018-02-15 | DeePhi Technology Co., Ltd. | Method for optimizing an artificial neural network (ann) |
CN108009625A (zh) * | 2016-11-01 | 2018-05-08 | 北京深鉴科技有限公司 | 人工神经网络定点化后的微调方法和装置 |
CN109688990A (zh) * | 2016-09-06 | 2019-04-26 | 新感知公司 | 用于向用户提供附属感觉信息的方法和*** |
CN110210618A (zh) * | 2019-05-22 | 2019-09-06 | 东南大学 | 动态修剪深度神经网络权重和权重共享的压缩方法 |
CN110276450A (zh) * | 2019-06-25 | 2019-09-24 | 交叉信息核心技术研究院(西安)有限公司 | 基于多粒度的深度神经网络结构化稀疏***和方法 |
CN110443359A (zh) * | 2019-07-03 | 2019-11-12 | 中国石油大学(华东) | 基于自适应联合剪枝-量化的神经网络压缩算法 |
CN110568445A (zh) * | 2019-08-30 | 2019-12-13 | 浙江大学 | 一种轻量化卷积神经网络的激光雷达与视觉融合感知方法 |
CN110880038A (zh) * | 2019-11-29 | 2020-03-13 | 中国科学院自动化研究所 | 基于fpga的加速卷积计算的***、卷积神经网络 |
Patent Citations (9)
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US20180046894A1 (en) * | 2016-08-12 | 2018-02-15 | DeePhi Technology Co., Ltd. | Method for optimizing an artificial neural network (ann) |
CN107679617A (zh) * | 2016-08-22 | 2018-02-09 | 北京深鉴科技有限公司 | 多次迭代的深度神经网络压缩方法 |
CN109688990A (zh) * | 2016-09-06 | 2019-04-26 | 新感知公司 | 用于向用户提供附属感觉信息的方法和*** |
CN108009625A (zh) * | 2016-11-01 | 2018-05-08 | 北京深鉴科技有限公司 | 人工神经网络定点化后的微调方法和装置 |
CN110210618A (zh) * | 2019-05-22 | 2019-09-06 | 东南大学 | 动态修剪深度神经网络权重和权重共享的压缩方法 |
CN110276450A (zh) * | 2019-06-25 | 2019-09-24 | 交叉信息核心技术研究院(西安)有限公司 | 基于多粒度的深度神经网络结构化稀疏***和方法 |
CN110443359A (zh) * | 2019-07-03 | 2019-11-12 | 中国石油大学(华东) | 基于自适应联合剪枝-量化的神经网络压缩算法 |
CN110568445A (zh) * | 2019-08-30 | 2019-12-13 | 浙江大学 | 一种轻量化卷积神经网络的激光雷达与视觉融合感知方法 |
CN110880038A (zh) * | 2019-11-29 | 2020-03-13 | 中国科学院自动化研究所 | 基于fpga的加速卷积计算的***、卷积神经网络 |
Non-Patent Citations (1)
Title |
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葛道辉等: "轻量级神经网络架构综述", 《软件学报》, vol. 31, no. 09, 5 December 2019 (2019-12-05), pages 2627 - 2653 * |
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