Open Access
| Issue |
BIO Web Conf.
Volume 129, 2024
The 17th European Microscopy Congress (EMC 2024)
|
|
|---|---|---|
| Article Number | 10037 | |
| Number of page(s) | 2 | |
| Section | Scanning Probe Microscopy: Imaging and Beyond | |
| DOI | https://doi.org/10.1051/bioconf/202412910037 | |
| Published online | 17 October 2024 | |
- He, K., Chen, X., Xie, S., Li, Y., Dollár, P. and Girshick, R., 2022. Masked autoencoders are scalable vision learners. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 16000–16009). [Google Scholar]
- Liu, Y., Zhang, S., Chen, J., Yu, Z., Chen, K. and Lin, D., 2023. Improving pixel-based mim by reducing wasted modeling capability. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 5361–5372). [Google Scholar]
- Chen, X., Xie, S. and He, K., 2021. An empirical study of training selfsupervised vision transformers. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 9640–9649). [Google Scholar]
- Aversa, R., Modarres, M.H., Cozzini, S., & Ciancio, R., 2018. NFFA- EUROPE - 100% SEM Dataset [Google Scholar]
- Conrad, R. and Narayan, K., 2021. CEM500K, a large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning. Elife, 10, p.e65894. [CrossRef] [PubMed] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.