Weld Bead Detection Based on 3D Geometric Features and Machine Learning Approaches-Reference-Cited by-同舟云学术

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Weld Bead Detection Based on 3D Geometric Features and Machine Learning Approaches

Published:2019 Issue: Volume:7 Page:14714-14727
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Rodriguez-Gonzalvez Pablo^ORCID,Rodriguez-Martin Manuel^ORCID

Funder

Universidad de León

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8600701/08604036.pdf?arnumber=8604036

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Weld quality measurement of T-joints based on three-dimensional scanner;The International Journal of Advanced Manufacturing Technology;2024-07-12

2. WeldNet: A voxel-based deep learning network for point cloud annular weld seam detection;Science China Technological Sciences;2024-03-27

3. Image-Based Weld Joint Type Classification Using Bag of Visual Words;Proceedings of Congress on Control, Robotics, and Mechatronics;2023-11-10

4. Implementation of Machine Learning Algorithms for Weld Quality Prediction and Optimization in Resistance Spot Welding;Journal of Materials Engineering and Performance;2023-07-17

5. Weld bead segmentation using RealSense depth camera based on 3D global features and texture features of subregions;Signal, Image and Video Processing;2023-01-21

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