Automatic Recognition of Multiple Weld Types Based on Structured Light Vision Sensor Using Deep Transfer Learning
Author:
Affiliation:
1. College of Automation Engineering, Shanghai University of Electric Power, Shanghai, China
Funder
National Natural Science Foundation of China
Shanghai Key Laboratory Power Station Automation Technology Laboratory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10089784/09969572.pdf?arnumber=9969572
Reference35 articles.
1. Automatic recognition system of welding seam type based on SVM method
2. A Random Forest-Based Automatic Inspection System for Aerospace Welds in X-Ray Images
3. Classification of welding joints based on wavelet transform and probabilistic neural network
4. Penetration state identification of lap joints in gas tungsten arc welding process based on two channel arc sounds
5. Wafer map defect recognition based on deep transfer learning-based densely connected convolutional network and deep forest
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