On-Demand Multiclass Imaging for Sample Scarcity in Industrial Environments

Author:

Orti Joan1ORCID,Moreno-Noguer Francesc1ORCID,Puig Vicenç1ORCID

Affiliation:

1. Institut de Robotica i Informatica Industrial, CSIC-UPC, Spain

Publisher

ACM

Reference24 articles.

1. abin24. 2021. Surface Inspection defect detection dataset. https://github.com/abin24/Surface-Inspection-defect-detection-dataset abin24. 2021. Surface Inspection defect detection dataset. https://github.com/abin24/Surface-Inspection-defect-detection-dataset

2. Increasing the robustness of material-specific deep learning models for crack detection across different materials

3. Selim Arikan , Kiran Varanasi , and Didier Stricker . 2019. Surface Defect Classification in Real-Time Using Convolutional Neural Networks. 1 ( 2019 ). arxiv:1904.04671http://arxiv.org/abs/1904.04671 Selim Arikan, Kiran Varanasi, and Didier Stricker. 2019. Surface Defect Classification in Real-Time Using Convolutional Neural Networks. 1 (2019). arxiv:1904.04671http://arxiv.org/abs/1904.04671

4. Synthetic Data Generation for Steel Defect Detection and Classification Using Deep Learning

5. Jakob Božič , Domen Tabernik , and Danijel Skočaj . 2020 . End-to-end training of a two-stage neural network for defect detection . Proceedings - International Conference on Pattern Recognition (2020 ), 5619–5626. https://doi.org/10.1109/ICPR48806.2021.9412092 arxiv:2007.07676 10.1109/ICPR48806.2021.9412092 Jakob Božič, Domen Tabernik, and Danijel Skočaj. 2020. End-to-end training of a two-stage neural network for defect detection. Proceedings - International Conference on Pattern Recognition (2020), 5619–5626. https://doi.org/10.1109/ICPR48806.2021.9412092 arxiv:2007.07676

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