Open Access
Issue
MATEC Web Conf.
Volume 392, 2024
International Conference on Multidisciplinary Research and Sustainable Development (ICMED 2024)
Article Number 01165
Number of page(s) 7
DOI https://doi.org/10.1051/matecconf/202439201165
Published online 18 March 2024
  1. V. Badrinarayanan, A. Kendall, and R. Cipolla. Segnet: A deep convolutional encoderdecoder architecture for image segmentation, 2015. [Google Scholar]
  2. C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs, 2016. [Google Scholar]
  3. A. P, A. Sharma, S. B. M, P. Pavankumar, N. K. Darwante and D. G. V, “Performance Monitoring and Dynamic Scaling Algorithm for Queue Based Internet of Things,” 2022 [Google Scholar]
  4. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), Chennai, India, 2022, pp. 1-7. [Google Scholar]
  5. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. Imagenet: A large-scale hierarchical image database. In 2009 IEEE Conference on Computer Vision and Pattern Recognition, pages 248–255, 2009. [Google Scholar]
  6. A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, and N. Houlsby. An image is worth 16x16 words: Transformers for image recognition at scale, 2020. [Google Scholar]
  7. K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition, 2015. [Google Scholar]
  8. Z. Huang, X. Wang, Y. Wei, L. Huang, H. Shi, W. Liu, and T. S. Huang. Ccnet: Criss-cross attention for semantic segmentation, 2018. [Google Scholar]
  9. T.-Y. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan, and S. Belongie. Feature pyramid networks for object detection, 2016. [Google Scholar]
  10. W. Liu, A. Rabinovich, and A. C. Berg. Parsenet: Looking wider to see better, 2015. [Google Scholar]
  11. Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, and B. Guo. Swin transformer: Hierarchical vision transformer using shifted windows, 2021. [Google Scholar]
  12. J. Long, E. Shelhamer, and T. Darrell. Fully convolutional networks for semantic segmentation, 2014. [Google Scholar]
  13. I. Loshchilov and F. Hutter. Decoupled weight decay regularization, 2017. [Google Scholar]
  14. C. Rupprecht, I. Laina, N. Navab, G. D. Hager, and F. Tombari. Guide me: Interacting with deep networks, 2018. [Google Scholar]
  15. T. Xiao, Y. Liu, B. Zhou, Y. Jiang, and J. Sun. Unified perceptual parsing for scene understanding, 2018. [Google Scholar]
  16. Y. Yuan, L. Huang, J. Guo, C. Zhang, X. Chen, and J. Wang. Ocnet: Object context network for scene parsing, 2018. [Google Scholar]
  17. H. Zhang, K. Dana, J. Shi, Z. Zhang, X. Wang, A. Tyagi, and A. Agrawal. Context encoding for semantic segmentation, 2018. [Google Scholar]
  18. H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia. Pyramid scene parsing network, 2016. [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.