CN109615627B - 一种输变电巡检图像质量评价方法及*** - Google Patents
一种输变电巡检图像质量评价方法及*** Download PDFInfo
- Publication number
- CN109615627B CN109615627B CN201811532907.7A CN201811532907A CN109615627B CN 109615627 B CN109615627 B CN 109615627B CN 201811532907 A CN201811532907 A CN 201811532907A CN 109615627 B CN109615627 B CN 109615627B
- Authority
- CN
- China
- Prior art keywords
- quality evaluation
- neural network
- image quality
- deep convolutional
- power transmission
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
Landscapes
- Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims (6)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811532907.7A CN109615627B (zh) | 2018-12-14 | 2018-12-14 | 一种输变电巡检图像质量评价方法及*** |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811532907.7A CN109615627B (zh) | 2018-12-14 | 2018-12-14 | 一种输变电巡检图像质量评价方法及*** |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109615627A CN109615627A (zh) | 2019-04-12 |
CN109615627B true CN109615627B (zh) | 2021-07-27 |
Family
ID=66009423
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811532907.7A Active CN109615627B (zh) | 2018-12-14 | 2018-12-14 | 一种输变电巡检图像质量评价方法及*** |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109615627B (zh) |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110210558B (zh) * | 2019-05-31 | 2021-10-26 | 北京市商汤科技开发有限公司 | 评估神经网络性能的方法及装置 |
CN111325711A (zh) * | 2020-01-16 | 2020-06-23 | 杭州德适生物科技有限公司 | 一种基于深度学习的染色体***相图像质量评价方法 |
CN111818363A (zh) * | 2020-07-10 | 2020-10-23 | 携程计算机技术(上海)有限公司 | 短视频提取方法、***、设备及存储介质 |
CN113158777B (zh) * | 2021-03-08 | 2024-07-02 | 佳都科技集团股份有限公司 | 质量评分方法、质量评分模型的训练方法及相关装置 |
CN113408695B (zh) * | 2021-04-29 | 2024-05-31 | 开放智能机器(上海)有限公司 | 一种离线量化工具的精度调优方法 |
CN113496485B (zh) * | 2021-06-24 | 2022-12-02 | 北京市遥感信息研究所 | 卫星遥感图像质量评价方法及装置 |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106503366A (zh) * | 2016-10-27 | 2017-03-15 | 石家庄铁道大学 | 抑制emd端点效应的方法 |
CN107743225A (zh) * | 2017-10-16 | 2018-02-27 | 杭州电子科技大学 | 一种利用多层深度表征进行无参考图像质量预测的方法 |
Family Cites Families (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103544705B (zh) * | 2013-10-25 | 2016-03-02 | 华南理工大学 | 一种基于深度卷积神经网络的图像质量测试方法 |
US9779492B1 (en) * | 2016-03-15 | 2017-10-03 | International Business Machines Corporation | Retinal image quality assessment, error identification and automatic quality correction |
US10002415B2 (en) * | 2016-04-12 | 2018-06-19 | Adobe Systems Incorporated | Utilizing deep learning for rating aesthetics of digital images |
CN107633513B (zh) * | 2017-09-18 | 2021-08-17 | 天津大学 | 基于深度学习的3d图像质量的度量方法 |
CN107610123A (zh) * | 2017-10-11 | 2018-01-19 | 中共中央办公厅电子科技学院 | 一种基于深度卷积神经网络的图像美学质量评价方法 |
CN108377387A (zh) * | 2018-03-22 | 2018-08-07 | 天津大学 | 基于3d卷积神经网络的虚拟现实视频质量评价方法 |
CN108596902B (zh) * | 2018-05-04 | 2020-09-08 | 北京大学 | 基于选通卷积神经网络的多任务全参考图像质量评价方法 |
CN108897797A (zh) * | 2018-06-12 | 2018-11-27 | 腾讯科技(深圳)有限公司 | 对话模型的更新训练方法、装置、存储介质及电子设备 |
CN108960087A (zh) * | 2018-06-20 | 2018-12-07 | 中国科学院重庆绿色智能技术研究院 | 一种基于多维度评估标准的人脸图像质量评估方法及*** |
-
2018
- 2018-12-14 CN CN201811532907.7A patent/CN109615627B/zh active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106503366A (zh) * | 2016-10-27 | 2017-03-15 | 石家庄铁道大学 | 抑制emd端点效应的方法 |
CN107743225A (zh) * | 2017-10-16 | 2018-02-27 | 杭州电子科技大学 | 一种利用多层深度表征进行无参考图像质量预测的方法 |
Also Published As
Publication number | Publication date |
---|---|
CN109615627A (zh) | 2019-04-12 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109615627B (zh) | 一种输变电巡检图像质量评价方法及*** | |
CN111739076B (zh) | 面向多种ct肺部纹理识别的非监督保内容域适应方法 | |
CN109559310B (zh) | 基于显著性检测的输变电巡检图像质量评价方法及*** | |
CN108615071B (zh) | 模型测试的方法及装置 | |
CN109858569A (zh) | 基于目标检测网络的多标签物体检测方法、***、装置 | |
CN110135282B (zh) | 一种基于深度卷积神经网络模型的考生回头抄袭作弊检测方法 | |
CN109214298B (zh) | 一种基于深度卷积网络的亚洲女性颜值评分模型方法 | |
CN111650453A (zh) | 基于加窗特征希尔伯特图像化的电力设备诊断方法及*** | |
CN114359727B (zh) | 基于轻量级优化Yolo v4的茶叶病害识别方法及*** | |
CN113313107A (zh) | 一种斜拉桥缆索表面多类型病害智能检测和识别方法 | |
CN116452904B (zh) | 图像美学质量确定方法 | |
CN110782448A (zh) | 渲染图像的评价方法及装置 | |
CN114881997A (zh) | 一种风电机组缺陷评估方法及相关设备 | |
CN114998251A (zh) | 一种基于联邦学***台地面异常检测方法 | |
CN115620178A (zh) | 一种用于无人机的电网异常危险行为的实时检测方法 | |
CN116665092A (zh) | 基于ia-yolov7的污水悬浮物识别方法及*** | |
CN113627302B (zh) | 一种登高施工合规性检测方法及*** | |
CN111539250B (zh) | 一种基于神经网络的图像雾浓度估计方法、***和终端 | |
CN116664823A (zh) | 基于元学习和度量学习的小样本sar目标检测识别方法 | |
Su | [Retracted] Data Research on Tobacco Leaf Image Collection Based on Computer Vision Sensor | |
CN117173595A (zh) | 基于改进YOLOv7的无人机航拍图像目标检测方法 | |
CN116229330A (zh) | 一种视频有效帧的确定方法、***、电子设备及存储介质 | |
Liu et al. | A novel image segmentation algorithm based on visual saliency detection and integrated feature extraction | |
CN111402397B (zh) | 基于无监督数据的tof深度数据优化方法及装置 | |
CN111259981A (zh) | 一种遥感图像处理后自动分类*** |
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 | ||
CB02 | Change of applicant information | ||
CB02 | Change of applicant information |
Address after: 250001, No. two, No. 150, Ji'nan, Shandong Applicant after: State Grid Shandong Electric Power Company Information Communication Company Applicant after: National Network Intelligent Technology Co., Ltd. Applicant after: State Grid Co., Ltd. Address before: 250001, No. two, No. 150, Ji'nan, Shandong Applicant before: State Grid Shandong Electric Power Company Information Communication Company Applicant before: Shandong Luneng Intelligent Technology Co., Ltd. Applicant before: State Grid Co., Ltd. |
|
TA01 | Transfer of patent application right | ||
TA01 | Transfer of patent application right |
Effective date of registration: 20201026 Address after: 250101 Electric Power Intelligent Robot Production Project 101 in Jinan City, Shandong Province, South of Feiyue Avenue and East of No. 26 Road (ICT Industrial Park) Applicant after: National Network Intelligent Technology Co.,Ltd. Address before: 250001, No. two, No. 150, Ji'nan, Shandong Applicant before: INFORMATION COMMUNICATION COMPANY OF STATE GRID SHANDONG ELECTRIC POWER Co. Applicant before: National Network Intelligent Technology Co.,Ltd. Applicant before: STATE GRID CORPORATION OF CHINA |
|
GR01 | Patent grant | ||
GR01 | Patent grant |