CN112106034A - 一种用于神经网络的卷积方法及装置 - Google Patents
一种用于神经网络的卷积方法及装置 Download PDFInfo
- Publication number
- CN112106034A CN112106034A CN201880093347.1A CN201880093347A CN112106034A CN 112106034 A CN112106034 A CN 112106034A CN 201880093347 A CN201880093347 A CN 201880093347A CN 112106034 A CN112106034 A CN 112106034A
- Authority
- CN
- China
- Prior art keywords
- data
- convolution
- neural network
- sampling
- processed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000013528 artificial neural network Methods 0.000 title claims abstract description 157
- 238000000034 method Methods 0.000 title claims abstract description 89
- 238000005070 sampling Methods 0.000 claims abstract description 148
- 238000004364 calculation method Methods 0.000 claims abstract description 39
- 238000012545 processing Methods 0.000 claims abstract description 35
- 239000013074 reference sample Substances 0.000 claims description 77
- 239000000523 sample Substances 0.000 claims description 55
- 238000004891 communication Methods 0.000 claims description 21
- 238000004590 computer program Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 abstract description 29
- 238000013135 deep learning Methods 0.000 abstract description 4
- 230000006870 function Effects 0.000 description 24
- 230000000875 corresponding effect Effects 0.000 description 15
- 238000010586 diagram Methods 0.000 description 9
- 230000033001 locomotion Effects 0.000 description 7
- 230000002093 peripheral effect Effects 0.000 description 6
- 230000001413 cellular effect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000005284 excitation Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000002596 correlated effect Effects 0.000 description 2
- 238000013500 data storage Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 230000005236 sound signal Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000004913 activation Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 210000004556 brain Anatomy 0.000 description 1
- 230000001276 controlling effect Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 235000019800 disodium phosphate Nutrition 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000010079 rubber tapping Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000010897 surface acoustic wave method Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Biomedical Technology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Image Analysis (AREA)
Abstract
本申请实施例提供一种用于神经网络的卷积方法及装置，涉及计算机技术领域，实现避免深度学习过程中的无效操作，以节约处理计算能力以及节省数据带宽。具体包括：对原始数据采样，以获取至少一个采样数据和该原始数据中除采样数据以外的至少一个剩余数据，剩余数据包括待处理剩余数据；当该参考采样数据与该卷积核的卷积结果不满足预设条件时，将该待处理剩余数据与卷积核的卷积结果设置为0。本申请用于卷积计算。
Description
PCT国内申请，说明书已公开。
Claims (15)
- PCT国内申请，权利要求书已公开。
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2018/095713 WO2020010639A1 (zh) | 2018-07-13 | 2018-07-13 | 一种用于神经网络的卷积方法及装置 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112106034A true CN112106034A (zh) | 2020-12-18 |
| CN112106034B CN112106034B (zh) | 2024-05-24 |
Family
ID=69142099
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201880093347.1A Active CN112106034B (zh) | 2018-07-13 | 2018-07-13 | 一种用于神经网络的卷积方法及装置 |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN112106034B (zh) |
| WO (1) | WO2020010639A1 (zh) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7444034B1 (en) * | 2002-11-06 | 2008-10-28 | Digivision, Inc. | Systems and methods for image enhancement in multiple dimensions |
| CN103384836A (zh) * | 2010-12-22 | 2013-11-06 | 皇家飞利浦电子股份有限公司 | 包含grappa算子的用于任意k空间轨迹的快速两步并行重建 |
| CN106022237A (zh) * | 2016-05-13 | 2016-10-12 | 电子科技大学 | 一种端到端的卷积神经网络的行人检测方法 |
| CN106326985A (zh) * | 2016-08-18 | 2017-01-11 | 北京旷视科技有限公司 | 神经网络训练方法和装置及数据处理方法和装置 |
| CN106971230A (zh) * | 2017-05-10 | 2017-07-21 | 中国石油大学(北京) | 基于深度学习的初至拾取方法及装置 |
| CN107563999A (zh) * | 2017-09-05 | 2018-01-09 | 华中科技大学 | 一种基于卷积神经网络的芯片缺陷识别方法 |
| WO2018120740A1 (zh) * | 2016-12-29 | 2018-07-05 | 深圳光启合众科技有限公司 | 图片分类方法和装置、机器人 |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9552510B2 (en) * | 2015-03-18 | 2017-01-24 | Adobe Systems Incorporated | Facial expression capture for character animation |
| US10762894B2 (en) * | 2015-03-27 | 2020-09-01 | Google Llc | Convolutional neural networks |
| CN104915322B (zh) * | 2015-06-09 | 2018-05-01 | 中国人民解放军国防科学技术大学 | 一种卷积神经网络硬件加速方法 |
| CN105260776B (zh) * | 2015-09-10 | 2018-03-27 | 华为技术有限公司 | 神经网络处理器和卷积神经网络处理器 |
| CN107995628A (zh) * | 2017-12-18 | 2018-05-04 | 北京工业大学 | 一种深度学习的认知无线网络多用户协作频谱感知方法 |
-
2018
- 2018-07-13 WO PCT/CN2018/095713 patent/WO2020010639A1/zh active Application Filing
- 2018-07-13 CN CN201880093347.1A patent/CN112106034B/zh active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7444034B1 (en) * | 2002-11-06 | 2008-10-28 | Digivision, Inc. | Systems and methods for image enhancement in multiple dimensions |
| CN103384836A (zh) * | 2010-12-22 | 2013-11-06 | 皇家飞利浦电子股份有限公司 | 包含grappa算子的用于任意k空间轨迹的快速两步并行重建 |
| CN106022237A (zh) * | 2016-05-13 | 2016-10-12 | 电子科技大学 | 一种端到端的卷积神经网络的行人检测方法 |
| CN106326985A (zh) * | 2016-08-18 | 2017-01-11 | 北京旷视科技有限公司 | 神经网络训练方法和装置及数据处理方法和装置 |
| WO2018120740A1 (zh) * | 2016-12-29 | 2018-07-05 | 深圳光启合众科技有限公司 | 图片分类方法和装置、机器人 |
| CN106971230A (zh) * | 2017-05-10 | 2017-07-21 | 中国石油大学(北京) | 基于深度学习的初至拾取方法及装置 |
| CN107563999A (zh) * | 2017-09-05 | 2018-01-09 | 华中科技大学 | 一种基于卷积神经网络的芯片缺陷识别方法 |
Non-Patent Citations (1)
| Title |
|---|
| 王昆;周骅;: "深度学习中的卷积神经网络***设计及硬件实现", 电子技术应用, no. 05 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112106034B (zh) | 2024-05-24 |
| WO2020010639A1 (zh) | 2020-01-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9507025B2 (en) | GPS positioning method for mobile terminal, and mobile terminal | |
| WO2018196390A1 (en) | Mobile terminal, method and device for displaying fingerprint recognition region | |
| CN110168487B (zh) | 一种触摸控制方法及装置 | |
| WO2019104677A1 (zh) | 不同屏显示不同的应用快捷菜单 | |
| US11012070B2 (en) | Electronic device and method thereof for grip recognition | |
| US20170109756A1 (en) | User Unsubscription Prediction Method and Apparatus | |
| US11394871B2 (en) | Photo taking control method and system based on mobile terminal, and storage medium | |
| CN107391198B (zh) | 任务调度方法和装置、计算机可读存储介质、移动终端 | |
| US9696428B2 (en) | Electronic device and method for measuring position information of electronic device | |
| CN110147742B (zh) | 一种关键点定位方法、装置及终端 | |
| CN110837343B (zh) | 处理快照的方法、装置及终端 | |
| CN110490295B (zh) | 一种数据处理方法及处理装置 | |
| EP3416130B1 (en) | Method, device and nonvolatile computer-readable medium for image composition | |
| CN104901992B (zh) | 一种资源转移的方法和装置 | |
| CN110083742B (zh) | 一种视频查询方法和装置 | |
| CN110708673A (zh) | 一种位置确定方法和便捷式多功能设备 | |
| CN109618278B (zh) | 一种定位方法及移动终端 | |
| CN116596202A (zh) | 工单处理方法、相关装置及存储介质 | |
| CN112106034B (zh) | 一种用于神经网络的卷积方法及装置 | |
| CN113672301A (zh) | 应用程序处理方法、移动终端及存储介质 | |
| CN107689909B (zh) | 用户显示方法及装置 | |
| CN110809234A (zh) | 一种人物类别识别方法和终端设备 | |
| CN117955095B (zh) | 电力负荷预测方法、装置、电子设备及存储介质 | |
| CN111382335B (zh) | 一种数据拉取方法、装置及存储介质 | |
| CN112733573B (zh) | 表格检测方法、装置、移动终端及存储介质 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |