CN114359300B - 一种图像分割模型的优化方法、装置、系统及存储介质 - Google Patents
一种图像分割模型的优化方法、装置、系统及存储介质 Download PDFInfo
- Publication number
- CN114359300B CN114359300B CN202210266768.8A CN202210266768A CN114359300B CN 114359300 B CN114359300 B CN 114359300B CN 202210266768 A CN202210266768 A CN 202210266768A CN 114359300 B CN114359300 B CN 114359300B
- Authority
- CN
- China
- Prior art keywords
- image segmentation
- loss function
- segmentation model
- calculating
- defect
- 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
- 238000003709 image segmentation Methods 0.000 title claims abstract description 195
- 238000000034 method Methods 0.000 title claims abstract description 150
- 238000005457 optimization Methods 0.000 title claims abstract description 66
- 238000003860 storage Methods 0.000 title claims abstract description 12
- 230000007547 defect Effects 0.000 claims abstract description 202
- 230000001629 suppression Effects 0.000 claims abstract description 46
- 230000006870 function Effects 0.000 claims description 252
- 238000002372 labelling Methods 0.000 claims description 48
- 238000004364 calculation method Methods 0.000 claims description 37
- 238000013135 deep learning Methods 0.000 claims description 14
- 230000005764 inhibitory process Effects 0.000 claims description 11
- 239000011159 matrix material Substances 0.000 claims description 8
- 238000009826 distribution Methods 0.000 claims description 2
- 238000012549 training Methods 0.000 abstract description 69
- 230000011218 segmentation Effects 0.000 description 31
- 238000005516 engineering process Methods 0.000 description 12
- 238000001514 detection method Methods 0.000 description 9
- 239000011248 coating agent Substances 0.000 description 8
- 238000000576 coating method Methods 0.000 description 8
- 230000007797 corrosion Effects 0.000 description 8
- 238000005260 corrosion Methods 0.000 description 8
- 230000002950 deficient Effects 0.000 description 8
- 239000002184 metal Substances 0.000 description 8
- 230000008569 process Effects 0.000 description 7
- 238000013459 approach Methods 0.000 description 6
- 230000000694 effects Effects 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- ORILYTVJVMAKLC-UHFFFAOYSA-N Adamantane Natural products C1C(C2)CC3CC1CC2C3 ORILYTVJVMAKLC-UHFFFAOYSA-N 0.000 description 3
- 229910000831 Steel Inorganic materials 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000007689 inspection Methods 0.000 description 3
- 239000010959 steel Substances 0.000 description 3
- 208000012639 Balance disease Diseases 0.000 description 2
- 238000005336 cracking Methods 0.000 description 2
- 125000004122 cyclic group Chemical group 0.000 description 2
- 238000013136 deep learning model Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 238000009776 industrial production Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000007115 recruitment Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000011179 visual inspection Methods 0.000 description 1
Images
Landscapes
- Image Analysis (AREA)
Abstract
Description
方法 | 类别1 | 类别2 | 类别3 | 类别4 | 全体 |
交叉熵 | 72% | 42% | 76% | 69% | 65% |
加权交叉熵 | 60% | 44% | 75% | 59% | 59% |
Focal | 68% | 61% | 82% | 69% | 70% |
Dice | 67% | 59% | 82% | 67% | 69% |
平衡损失函数 | 82% | 76% | 95% | 89% | 87% |
Claims (13)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210266768.8A CN114359300B (zh) | 2022-03-18 | 2022-03-18 | 一种图像分割模型的优化方法、装置、系统及存储介质 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210266768.8A CN114359300B (zh) | 2022-03-18 | 2022-03-18 | 一种图像分割模型的优化方法、装置、系统及存储介质 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN114359300A CN114359300A (zh) | 2022-04-15 |
CN114359300B true CN114359300B (zh) | 2022-06-28 |
Family
ID=81094404
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210266768.8A Active CN114359300B (zh) | 2022-03-18 | 2022-03-18 | 一种图像分割模型的优化方法、装置、系统及存储介质 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114359300B (zh) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115049547B (zh) * | 2022-08-16 | 2022-10-21 | 成都数之联科技股份有限公司 | 一种航拍图像实时增量拼接方法及系统及装置及介质 |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP3171297A1 (en) * | 2015-11-18 | 2017-05-24 | CentraleSupélec | Joint boundary detection image segmentation and object recognition using deep learning |
CN110246149A (zh) * | 2019-05-28 | 2019-09-17 | 西安交通大学 | 基于深度加权全卷积网络的室内场景迁移分割方法 |
CN111696117A (zh) * | 2020-05-20 | 2020-09-22 | 北京科技大学 | 一种基于骨架感知的损失函数加权方法及装置 |
CN111831956A (zh) * | 2020-06-16 | 2020-10-27 | 五邑大学 | 高自由度类不平衡性损失函数的调整方法和存储介质 |
CN112541864A (zh) * | 2020-09-25 | 2021-03-23 | 中国石油大学(华东) | 一种基于多尺度生成式对抗网络模型的图像修复方法 |
CN113283434A (zh) * | 2021-04-13 | 2021-08-20 | 北京工业大学 | 一种基于分割网络优化的图像语义分割方法及系统 |
EP3961561A1 (en) * | 2020-08-26 | 2022-03-02 | Siemens Healthcare GmbH | Method for designing a module for image segmentation |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111260665B (zh) * | 2020-01-17 | 2022-01-21 | 北京达佳互联信息技术有限公司 | 图像分割模型训练方法和装置 |
CN111898406B (zh) * | 2020-06-05 | 2022-04-29 | 东南大学 | 基于焦点损失和多任务级联的人脸检测方法 |
CN113591529A (zh) * | 2021-02-23 | 2021-11-02 | 腾讯科技(深圳)有限公司 | 动作分割模型的处理方法、装置、计算机设备和存储介质 |
-
2022
- 2022-03-18 CN CN202210266768.8A patent/CN114359300B/zh active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP3171297A1 (en) * | 2015-11-18 | 2017-05-24 | CentraleSupélec | Joint boundary detection image segmentation and object recognition using deep learning |
CN110246149A (zh) * | 2019-05-28 | 2019-09-17 | 西安交通大学 | 基于深度加权全卷积网络的室内场景迁移分割方法 |
CN111696117A (zh) * | 2020-05-20 | 2020-09-22 | 北京科技大学 | 一种基于骨架感知的损失函数加权方法及装置 |
CN111831956A (zh) * | 2020-06-16 | 2020-10-27 | 五邑大学 | 高自由度类不平衡性损失函数的调整方法和存储介质 |
EP3961561A1 (en) * | 2020-08-26 | 2022-03-02 | Siemens Healthcare GmbH | Method for designing a module for image segmentation |
CN112541864A (zh) * | 2020-09-25 | 2021-03-23 | 中国石油大学(华东) | 一种基于多尺度生成式对抗网络模型的图像修复方法 |
CN113283434A (zh) * | 2021-04-13 | 2021-08-20 | 北京工业大学 | 一种基于分割网络优化的图像语义分割方法及系统 |
Non-Patent Citations (3)
Title |
---|
A novel active contour model based on modified symmetric cross entropy for remote sensing river image segmentation;Bin Han 等;《Remote Sensing》;20170228;1-32 * |
基于改进的U-Net肺结节分割方法研究;苗语 等;《计算机应用与软件》;20211212;第38卷(第12期);213-219 * |
基于特征选择与残差融合的肝肿瘤分割模型;乔伟晨 等;《中国图象图形学报》;20220316;838-849 * |
Also Published As
Publication number | Publication date |
---|---|
CN114359300A (zh) | 2022-04-15 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110660052B (zh) | 一种基于深度学习的热轧带钢表面缺陷检测方法 | |
CN109509187B (zh) | 一种针对大分辨率布匹图像中的小瑕疵的高效检验算法 | |
CN110211097A (zh) | 一种基于Faster R-CNN参数迁移的裂缝图像检测方法 | |
WO2022012110A1 (zh) | 胚胎光镜图像中细胞的识别方法及系统、设备及存储介质 | |
CN111815564B (zh) | 一种检测丝锭的方法、装置及丝锭分拣系统 | |
CN111428733B (zh) | 基于语义特征空间转换的零样本目标检测方法及系统 | |
CN109934826A (zh) | 一种基于图卷积网络的图像特征分割方法 | |
CN108304775A (zh) | 遥感图像识别方法、装置、存储介质以及电子设备 | |
WO2020238256A1 (zh) | 基于弱分割的损伤检测方法及装置 | |
CN108961230B (zh) | 结构表面裂缝特征的识别与提取方法 | |
CN107507170A (zh) | 一种基于多尺度图像信息融合的机场跑道裂缝检测方法 | |
CN110543906B (zh) | 基于Mask R-CNN模型的肤质自动识别方法 | |
CN116012291A (zh) | 工业零件图像缺陷检测方法及系统、电子设备和存储介质 | |
CN112365497A (zh) | 基于TridentNet和Cascade-RCNN结构的高速目标检测方法和系统 | |
CN114359300B (zh) | 一种图像分割模型的优化方法、装置、系统及存储介质 | |
CN112819748A (zh) | 一种带钢表面缺陷识别模型的训练方法及装置 | |
CN111696079A (zh) | 一种基于多任务学习的表面缺陷检测方法 | |
CN117392042A (zh) | 缺陷检测方法、缺陷检测设备及存储介质 | |
CN109993728B (zh) | 一种热转印胶水偏位自动检测方法和系统 | |
CN115797314A (zh) | 零件表面缺陷检测方法、系统、设备及存储介质 | |
CN117274212A (zh) | 一种桥梁水下结构裂缝检测方法 | |
CN112084941A (zh) | 一种基于遥感图像的目标检测与识别方法 | |
CN116977237A (zh) | 一种图像处理方法、系统及电子设备 | |
Zheng et al. | Improved Yolo V3 for steel surface defect detection | |
CN115661126A (zh) | 一种基于改进YOLOv5算法的带钢表面缺陷检测方法 |
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 | ||
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20220804 Address after: 400039 Chongqing Jiulongpo Yuzhou Road No. 33 Patentee after: NO 59 Research Institute OF CHINA ORDNACE INDUSTRY Patentee after: Chengdu shuzhilian Technology Co.,Ltd. Address before: 610000 No. 270, floor 2, No. 8, Jinxiu street, Wuhou District, Chengdu, Sichuan Patentee before: Chengdu shuzhilian Technology Co.,Ltd. |
|
TR01 | Transfer of patent right |
Effective date of registration: 20240826 Address after: 400039 Chongqing Jiulongpo Yuzhou Road No. 33 Patentee after: Southwest Institute of technology and engineering of China Ordnance Equipment Group Country or region after: China Patentee after: Chengdu shuzhilian Technology Co.,Ltd. Address before: 400039 Chongqing Jiulongpo Yuzhou Road No. 33 Patentee before: NO 59 Research Institute OF CHINA ORDNACE INDUSTRY Country or region before: China Patentee before: Chengdu shuzhilian Technology Co.,Ltd. |