no code implementations • IEEE Access, vol. 8, pp. 16155-16165 2020 • H. Wu, M. Cao, A. Wang, M. Wang
The results show that, compared with the traditional deep convolution model, OctConv-CapsNet can improve the classification accuracy of LiDAR-DSM data, and when the number of training samples of the experiment is 800, the classification accuracies reached 96. 12% and 96. 79% on Bayview Park and Recology datasets, respectively.
no code implementations • 16 Nov 2006 • W. P. Chen, C. Alcock, T. Axelrod, F. B. Bianco, Y. I. Byun, Y. H. Chang, K. H. Cook, R. Dave, J. Giammarco, D. W. Kim, S. K. King, T. Lee, M. Lehner, C. C. Lin, H. C. Lin, J. J. Lissauer, S. Marshall, N. Meinshausen, S. Mondal, I. de Pater, R. Porrata, J. Rice, M. E. Schwamb, A. Wang, S. Y. Wang, C. Y. Wen, Z. W. Zhang
Because a typical occultation event by a TNO a few km across will last for only a fraction of a second, fast photometry is necessary.
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