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Research Papers

An Efficient Internet Map Tiles Rendering Approach on High Resolution Devices

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References

  • Bei, W., Guo, M., and Huang, Y., 2019. A spatial adaptive algorithm framework for building pattern recognition using graph convolutional networks. Sensors, 19 (24), 5518. doi:10.3390/s19245518
  • Chao, D., et al., 2014. Learning a deep convolutional network for image super-resolution. Proceedings of the 13th European conference on computer vision, Zurich, Switzerland: Springer, 184–199.
  • Dong, C., et al. 2016. Image super-resolution using deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38 (2), 295–307. doi:10.1109/TPAMI.2015.2439281
  • Guo, M., and Guan, Q., et al. 2015. A spatially adaptive decomposition approach for parallel vector data visualization of polylines and polygons. International Journal of Geographical Information Science, 29 (8), 1419–1440. doi:10.1080/13658816.2015.1032294
  • Guo, M., and Han, C. et al. 2020. A universal parallel scheduling approach to polyline and polygon vector data buffer analysis on conventional GIS platforms. Transactions in GIS, 24 (6), 1630–1654. doi:10.1111/tgis.12670
  • Guo, M., and Han, C., et al. 2021. A novel truncated nonconvex nonsmooth variational method for SAR image despeckling. Remote Sensing Letters, 12 (2), 174–183. doi:10.1080/2150704X.2020.1846820
  • Guo, M., et al. 2017. An efficient data organization and scheduling strategy for accelerating large vector data rendering. Transactions in GIS, 21 (6), 1217–1236. doi:10.1111/tgis.12275
  • Guo, M., Huang, Y., and Xie, Z., 2015. A balanced decomposition approach to real-time visualization of large vector maps in cybergis. Frontiers of Computer Science, 9 (3), 442–455. doi:10.1007/s11704-014-3498-7
  • Guo, M., and Liu, H., et al. 2020. Building extraction based on u-net with an attention block and multiple losses. Remote Sensing, 12 (9), 1400. doi:10.3390/rs12091400
  • Guo, M., and Song, Z., et al. 2021. Mesh denoising via adaptive consistent neighborhood. Sensors, 21 (2), 412. doi:10.3390/s21020412
  • Guo, M., and Wu, L., et al., 2021. An efficient internet map tiles rendering approach on high resolution devices. Figshare, Figure. doi:10.6084/m9.figshare.13578212.v2
  • Ha, V.K., et al. 2019. Deep learning based single image super-resolution: a survey. International Journal of Automation and Computing, 16 (4), 413–426. doi:10.1007/s11633-019-1183-x
  • Hou, H.S. and Andrews, H.C., 1978. Cubic splines for image interpolation and digital filtering. IEEE Transactions on Acoustics Speech and Signal Processing, 26 (6), 508–517. doi:10.1109/TASSP.1978.1163154
  • Keys, R.G., 1981. Cubic convolution interpolation for digital image processing. IEEE Transactions on Acoustics Speech and Signal Processing, 29 (6), 1153–1160. doi:10.1109/TASSP.1981.1163711
  • Kim, J., et al., 2016. Accurate image super-resolution using very deep convolutional networks. Proceedings of 2016 IEEE conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, USA, 1646–1654.
  • Ma, T., et al., 2014. Optimized Laplacian image sharpening algorithm based on graphic processing unit. Physica A Statistical Mechanics & Its Applications, 416, 400–410. doi:10.1016/j.physa.2014.09.026
  • Nuno-Maganda, M.A. and Arias-Estrada, M.O., 2005. Real-time FPGA-based architecture for bicubic interpolation: an application for digital image scaling. Proceedings of the 2005 international conference on reconfigurable computing and FPGAs, IEEE. Puebla, Mexico.
  • Pattanasethanon, P. and Attachoo, B., 2009. A unified histogram and laplacian based for image sharpening. Proceedings of the 9th international symposium on communications and information technology. Icheon, South Korea.
  • Russo, F., 2002. An image enhancement technique combining sharpening and noise reduction. Instrumentation & Measurement IEEE Transactions, 51 (4), 824–828. doi:10.1109/TIM.2002.803394
  • Wang, S., et al. 2013. CyberGIS software: a synthetic review and integration roadmap. International Journal of Geographical Information Science, 27 (11), 2122–2145. doi:10.1080/13658816.2013.776049
  • Yang, C., et al. 2005. Performance-improving techniques in web-based GIS. International Journal of Geographical Information Science, 19 (3), 319–342. doi:10.1080/13658810412331280202

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