Efficient surface finish defect detection using reduced rank spline smoothers and probabilistic classifiers

Author:

Pya Arnqvist NatalyaORCID,Ngendangenzwa Blaise,Lindahl Eric,Nilsson Leif,Yu JunORCID

Funder

Strategic Vehicle Program Research and Innovation

VINNOVA - Sweden’s Innovation Agency

Publisher

Elsevier BV

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Statistics and Probability

Reference39 articles.

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2. Detecting dings and dents on specular car body surfaces based on optical flow;Arnal;Journal of Manufacturing Systems,2017

3. Beygelzimer, A., Kakadet, S., Langford, J., Arya, S., Mount, D., Li, S., 2018. FNN: Fast Nearest Neighbor Search Algorithms and Applications.  R package version 1.1.2.2.

4. Pattern Recognition and Machine Learning;Bishop,2007

5. A bayesian reassessment of nearest-neighbor classification;Cucala;Journal of the American Statistical Association,2009

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1. Detecting and classifying defects on the surface of water heaters: Development of an automated system;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2024-08-01

2. Machine Intelligence for Detection of Dents and Scratches on Car Body;2023 OITS International Conference on Information Technology (OCIT);2023-12-13

3. Automatic Selection of White Paint Types for Automotive Industry;2022 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC);2022-11-09

4. Imbalanced classification: A paradigm‐based review;Statistical Analysis and Data Mining: The ASA Data Science Journal;2021-08-02

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