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检索条件"主题词=Defect segmentation"
104 条 记 录,以下是41-50 订阅
排序:
Trans-DCN: A High-Efficiency and Adaptive Deep Network for Bridge Cable Surface defect segmentation
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REMOTE SENSING 2024年 第15期16卷 2711页
作者: Huang, Zhihai Guo, Bo Deng, Xiaolong Guo, Wenchao Min, Xing Guangdong Univ Technol Sch Civil & Transportat Engn Guangzhou 510006 Peoples R China Shenzhen Univ Sch Architecture & Urban Planning Shenzhen 518060 Peoples R China Guangdong Metro Design Res Inst Co Ltd Guangzhou 510499 Peoples R China
Cables are vital load-bearing components of cable-stayed bridges. Surface defects can lead to internal corrosion and fracturing, significantly impacting the stability of the bridge structure. The detection of surface ... 详细信息
来源: 评论
EDSV-Net: An efficient defect segmentation network based on visual attention and visual perception
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EXPERT SYSTEMS WITH APPLICATIONS 2024年 第PartB期237卷
作者: Huang, Yanqing Jing, Junfeng Sheng, Siyu Wang, Zhen Xian Polytech Univ Coll Elect & Informat Xian 710048 Peoples R China
In industrial production, surface defect detection algorithms based on convolutional neural networks have been widely studied to improve production quality. However, for practical applications, there are still many is... 详细信息
来源: 评论
A digital assistance system leveraging vision foundation models & 3D localization for reproducible defect segmentation in visual inspection
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Procedia CIRP 2024年 130卷 387-397页
作者: J. Koch D. Jevremovic K. Moenck T. Schüppstuhl Hamburg University of Technology Institute of Aircraft Production Technology Denickestr. 17 21073 Hamburg Germany
In response to the limitations of manual visual inspection in manufacturing industries, this paper presents a novel approach that combines Meta AI’s Segment Anything Model (SAM) as a current representative of a visio... 详细信息
来源: 评论
Region- and Strength-Controllable GAN for defect Generation and segmentation in Industrial Images
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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2022年 第7期18卷 4531-4541页
作者: Niu, Shuanlong Li, Bin Wang, Xinggang Peng, Yaru Huazhong Univ Sci & Technol Sch Mech Sci & Engn Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Elect Informat & Commun Wuhan 430074 Peoples R China
Deep learning for computer vision has achieved remarkable results based on massive, diverse, and well-annotated training sets. However, it is difficult to collect defect datasets that cover all possible features, espe... 详细信息
来源: 评论
Human-Machine Hybrid Strategy for defect Semantic segmentation With Limited Data
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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷 1页
作者: Shan, Dexing Zhang, Yunzhou Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China
In the field of industrial intelligent inspection, two problems need to be solved urgently. One is how to integrate complex industrial inspection expertise into algorithms. The second is how to predict other similar p... 详细信息
来源: 评论
Fabric defect Image segmentation Method Based on The Combination of Canny and Morphology  34
Fabric Defect Image Segmentation Method Based on The Combina...
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34th Chinese Control and Decision Conference (CCDC)
作者: Liu, Meiju Xu, Wenqiong Lin, Zixiang Dai, Yingxu Shenyang Jianzhu Univ Sch Informat & Control Engn Shenyang 110168 Peoples R China
In order to filter out the background noise while retaining the characteristics of the defects, this paper combines Canny and morphological processing to segment the fabric defects. After image preprocessing, our impr... 详细信息
来源: 评论
Steering knuckle surface defect detection and segmentation based on reverse residual distillation
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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 第PartB期137卷
作者: Zhou, Shuaijie Cheng, Shuhong Zhang, Dianfan Wang, Zedai Zhang, Shijun Zhu, Yujie Wang, Hongbo Yanshan Univ Inst Elect Engn Qinhuangdao 066004 Hebei Peoples R China Yanshan Univ Hebei Key Lab Special Delivery Equipment Qinhuangdao 066004 Hebei Peoples R China BYD Automot Engn Res Inst Shenzhen 518118 Peoples R China Weichai Lovol Intelligent Agr Technol CO LTD Weifang 261206 Peoples R China Fudan Univ Acad Engn & Technol Shanghai 200433 Peoples R China
Although the supervised deep learning method effectively detects and segments the surface defects of the steering knuckle, in the absence of sufficient defect samples, the model is prone to tend to learn normal sample... 详细信息
来源: 评论
defect Detection and segmentation Framework for Remote Field Eddy Current Sensor Data
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SENSORS 2017年 第10期17卷 2276页
作者: Falque, Raphael Vidal-Calleja, Teresa Miro, Jaime Valls Univ Technol Sydney Ctr Autonomous Syst CB 11 09 300 Fac Engn & Informat Technol 15 Broadway Ultimo NSW 2007 Australia
Remote-Field Eddy-Current (RFEC) technology is often used as a Non-Destructive Evaluation (NDE) method to prevent water pipe failures. By analyzing the RFEC data, it is possible to quantify the corrosion present in pi... 详细信息
来源: 评论
Fabric defect Image segmentation Method Based on The Combination of Canny and Morphology
Fabric Defect Image Segmentation Method Based on The Combina...
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第34届中国控制与决策会议
作者: Meiju Liu Wenqiong Xu Zixiang Lin Yingxu Dai School of Information and Control Engineering Shenyang Jianzhu University
In order to filter out the background noise while retaining the characteristics of the defects,this paper combines Canny and morphological processing to segment the fabric *** image preprocessing,our improved algorith... 详细信息
来源: 评论
A self-configuring transformer segmentation method for welding radiographic defect detection in steel pipes
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NONDESTRUCTIVE TESTING AND EVALUATION 2025年
作者: Guan, Keming Zhou, Yifeng Wang, Li Chang, Baohua Du, Dong Tsinghua Univ Dept Mech Engn Beijing Peoples R China Tsinghua Univ Key Lab Adv Mat Proc Technol Minist Educ Beijing Peoples R China
Radiography is a primary non-destructive testing method and is crucial for ensuring the quality of steel pipe welds. Although deep learning-based methods have shown significant achievements, they still encounter subje... 详细信息
来源: 评论