3D Point Cloud-Based Lithium Battery Surface Defects Detection Using Region Growing Proposal Approach

Author:

Rehman Zia Ur,Wang Xin,Alsumeri Abdulrahman Abdo Ali,Khan Malak Abid Ali,Ma Hongbin

Publisher

Springer Nature Singapore

Reference18 articles.

1. Qian, Q., et al.: The role of structural defects in commercial lithium-ion batteries. Cell Reports Phys. Sci. 2(9) (2021)

2. Aamir, S.Y., Aaqib, M.: Real-Time Object Detection in Occluded Environment with Background Cluttering Effects Using Deep Learning. IWACIII2021

3. Qi, C.R., Chen, X., Litany, O., Guibas, L.J.: Imvotenet: Boosting 3d object detection in point clouds with image votes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 4404–4413 (2020)

4. Mirani, M.I.K., Chen, T., Khan, M.A.A., Aamir, S.M., Menhaj, W.: Object Recognition in Different Lighting Conditions at Various Angles by Deep Learning Method. arXiv preprint arXiv:2210.09618 (2022)

5. Khameneifar, F., Feng, H.Y.: Extracting sectional contours from scanned point clouds via adaptive surface projection. Int. J. Prod. Res. 55, 4466–4480 (2017)

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