Author:
Haseena Rahmath P.,Chaurasia Kuldeep
Publisher
Springer Nature Switzerland
Reference19 articles.
1. Chen, M., Wei, Z., Huang, Z., Ding, B., Li, Y.: Simple and deep graph convolutional networks. In: International Conference on Machine Learning, pp. 1725–1735. PMLR (2020)
2. Hamilton, W., Ying, Z., Leskovec, J.: Inductive representation learning on large graphs. Adv. Neural Inform. Process. Syst. 30 (2017)
3. Haseena Rahmath, P., Srivastava, V., Chaurasia, K.: A strategy to accelerate the inference of a complex deep neural network. In: Proceedings of Data Analytics and Management: ICDAM 2022, pp. 57–68. Springer (2023). https://doi.org/10.1007/978-981-19-7615-5_5
4. Hong, D., Gao, L., Yao, J., Zhang, B., Plaza, A., Chanussot, J.: Graph convolutional networks for hyperspectral image classification. IEEE Trans. Geosci. Remote Sens. 59(7), 5966–5978 (2020)
5. Hong, D., Gao, L., Yao, J., Zhang, B., Plaza, A., Chanussot, J.: Graph convolutional networks for hyperspectral image classification. IEEE Trans. Geosci. Remote Sens. 59(7), 5966–5978 (2021). https://doi.org/10.1109/TGRS.2020.3015157