MultiCut-MultiMix: a two-level data augmentation method for detecting small and densely distributed objects in large-size images-Reference-Cited by-同舟云学术

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MultiCut-MultiMix: a two-level data augmentation method for detecting small and densely distributed objects in large-size images

Published:2023-06-19 Issue: Volume: Page:
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Xin Zhimeng,Lu Tongwei,Li Yuzhou,You Xinge

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s00371-023-02920-z.pdf

Reference45 articles.

1. Lorenz, K.S., Serrano, F., Salama, P., Delp, E.J.: Segmentation and registration based analysis of microscopy images. In: Proceedings of International Conference on Image Processing (ICIP), Cairo, Egypt, pp. 4213–4216 (2009)

2. Rohith, G., Kumar, L.S.: Paradigm shifts in super-resolution techniques for remote sensing applications. Vis. Comput. 37(7), 1965–2008 (2021)

3. Hua, W., Wang, R., Zeng, X., Tang, Y., Wang, H., Bao, H.: Compressing repeated content within large-scale remote sensing images. Vis. Comput. 28(6), 755–764 (2012)

4. Shawky, O.A., Hagag, A., El-Dahshan, E.-S.A., Ismail, M.A.: Remote sensing image scene classification using CNN-MLP with data augmentation. Optik 221, 165356 (2020)

5. Wu, M., Jin, X., Jiang, Q., Lee, S.-J., Liang, W., Lin, G., Yao, S.: Remote sensing image colorization using symmetrical multi-scale DCGAN in YUV color space. Vis. Comput. 37(7), 1707–1729 (2021)

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