Open Access
Issue |
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|
|
---|---|---|
Article Number | 02003 | |
Number of page(s) | 9 | |
Section | 2 - Offline Computing | |
DOI | https://doi.org/10.1051/epjconf/202024502003 | |
Published online | 16 November 2020 |
- CMS Collaboration, The Phase-2 Upgrade of the CMS Endcap Calorimeter, CERN-LHCC-2017-023. CMS-TDR-019 (2017), https://cds.cern.ch/record/2293646 [Google Scholar]
- CMS Collaboration, JINST 3 S08004 (2008) [Google Scholar]
- S. R. Qasim, J. Kieseler, Y. Iiyama, et al., Eur. Phys. J. C 79: 608 (2019), https://doi.org/10.1140/epjc/s10052-019-7113-9 [CrossRef] [EDP Sciences] [Google Scholar]
- https://www.kaggle.com [Google Scholar]
- T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollar, and C. L. Zitnick, Microsoft COCO: Common objects in context, European Conference on Computer Vision ECCV 8693 (2014) [Google Scholar]
- K. He, G. Gkioxari, P. Dollár, R. Girshick, Mask R-CNN, IEEE International Conference on Computer Vision ICCV (2017) [Google Scholar]
- R. B. Girshick, J. Donahue, T. Darrell, J. Malik, Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation, IEEE Conference on Computer Vision and Pattern Recognition (2014), https://doi.org/10.1109/CVPR.2014.81 [Google Scholar]
- R. Girshick, Fast R-CNN, IEEE International Conference on Computer Vision ICCV (2015) [Google Scholar]
- S. Ren, K. He, R. Girshick, and J. Sun, Faster R-CNN: Towards real-time object detection with region proposal networks, Advances in Neural Information Processing Systems NIPS (2015). [Google Scholar]
- J. Huang, V. Rathod, C. Sun, M. Zhu, A. Korattikara, A. Fathi, I. Fischer, Z. Wojna, Y. Song, S. Guadarrama, et al., Speed/accuracy trade-offs for modern convolutional object detectors, IEEE Conference on Computer Vision and Pattern Recognition CVPR (2017) [Google Scholar]
- W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, A. C. Berg, SSD: Single Shot MultiBox Detector, European Conference on Computer Vision ECCV (2016), doi:10.1007/978-3-319-46448-0_2 [Google Scholar]
- J. Redmon, S. Divvala, R. Girshick, A. Farhadi, You Only Look Once: Unified, RealTime Object Detection, IEEE Conference on Computer Vision and Pattern Recognition -CVPR (2016), DOI: 10.1109/CVPR.2016.91 [Google Scholar]
- R. Girshick, I. Radosavovic, G. Gkioxari, P. Dollár and K. He, Detectron Object Detection implementations, https://github.com/facebookresearch/detectron (2018) [Google Scholar]
- T.-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, S. Belongie, Feature Pyramid Networks for Object Detection, IEEE Conference on Computer Vision and Pattern Recognition CVPR (2017) [Google Scholar]
- K. He, X. Zhang, S. Ren, and J. Sun, Deep residual learning for image recognition, IEEE Conference on Computer Vision and Pattern Recognition CVPR (2016) [Google Scholar]
- N. Bodla, B. Singh, R. Chellappa, L. S. Davis, Soft-NMS Improving Object Detection with One Line of Code, IEEE International Conference on Computer Vision ICCV (2017) [Google Scholar]
- Z. Zhang and M. R. Sabuncu, Generalized cross entropy loss for training deep neural networks with noisy labels, Proceedings of the 32nd International Conference on Neural Information Processing Systems, pages 8792-8802, NIPS (2018) [Google Scholar]
- Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow, W. Abdulla (2017), https://github.com/matterport/Mask_RCNN [Google Scholar]
- P. Jaeger et al., Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection”, Machine Learning for Health (ML4H) at NeurIPS (2019), https://arxiv.org/abs/1811.08661 [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.