| Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data P Gong, J Wang, L Yu, Y Zhao, Y Zhao, L Liang, Z Niu, X Huang, H Fu, ... International Journal of Remote Sensing 34 (7), 2607-2654, 2013 | 984 | 2013 |
| The Sunway TaihuLight supercomputer: system and applications H Fu, J Liao, J Yang, L Wang, Z Song, X Huang, C Yang, W Xue, F Liu, ... Science China Information Sciences 59 (7), 1-16, 2016 | 353 | 2016 |
| Deep learning based oil palm tree detection and counting for high-resolution remote sensing images W Li, H Fu, L Yu, A Cracknell Remote Sensing 9 (1), 22, 2017 | 206 | 2017 |
| Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017 B Chen, B Xu, Z Zhu, C Yuan, HP Suen, J Guo, N Xu, W Li, Y Zhao, ... Sci. Bulletin 64 (6), 370-373, 2019 | 176 | 2019 |
| Managing nitrogen to restore water quality in China CQ Yu, X Huang, H Chen, HCJ Godfray, JS Wright, JW Hall, P Gong, ... Nature 567 (7749), 516-520, 2019 | 167 | 2019 |
| Stacked Autoencoder-based deep learning for remote-sensing image classification: a case study of African land-cover mapping W Li, H Fu, L Yu, P Gong, D Feng, C Li, N Clinton International journal of remote sensing 37 (23), 5632-5646, 2016 | 94 | 2016 |
| Beyond traditional microprocessors for geoscience high-performance computing applications O Lindtjorn, R Clapp, O Pell, H Fu, M Flynn, O Mencer Ieee Micro 31 (2), 41-49, 2011 | 94 | 2011 |
| Selecting the right hardware for reverse time migration RG Clapp, H Fu, O Lindtjorn The leading edge 29 (1), 48-58, 2010 | 86 | 2010 |
| 10M-core scalable fully-implicit solver for nonhydrostatic atmospheric dynamics C Yang, W Xue, H Fu, H You, X Wang, Y Ao, F Liu, L Gan, P Xu, L Wang, ... SC'16: Proceedings of the International Conference for High Performance …, 2016 | 83 | 2016 |
| F-CNN: An FPGA-based framework for training convolutional neural networks W Zhao, H Fu, W Luk, T Yu, S Wang, B Feng, Y Ma, G Yang 2016 IEEE 27Th international conference on application-specific systems …, 2016 | 74 | 2016 |
| A peta-scalable CPU-GPU algorithm for global atmospheric simulations C Yang, W Xue, H Fu, L Gan, L Li, Y Xu, Y Lu, J Sun, G Yang, W Zheng ACM SIGPLAN Notices 48 (8), 1-12, 2013 | 68 | 2013 |
| 9-Pflops nonlinear earthquake simulation on Sunway TaihuLight: enabling depiction of 18-Hz and 8-meter scenarios H Fu, C He, B Chen, Z Yin, Z Zhang, W Zhang, T Zhang, W Xue, W Liu, ... Proceedings of the International Conference for High Performance Computing …, 2017 | 67 | 2017 |
| Enabling and scaling a global shallow-water atmospheric model on Tianhe-2 W Xue, C Yang, H Fu, X Wang, Y Xu, L Gan, Y Lu, X Zhu 2014 IEEE 28th international parallel and distributed processing symposium …, 2014 | 60 | 2014 |
| Understanding data characteristics and access patterns in a cloud storage system S Liu, X Huang, H Fu, G Yang 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid …, 2013 | 60 | 2013 |
| Ultra-scalable CPU-MIC acceleration of mesoscale atmospheric modeling on Tianhe-2 W Xue, C Yang, H Fu, X Wang, Y Xu, J Liao, L Gan, Y Lu, R Ranjan, ... IEEE Transactions on Computers 64 (8), 2382-2393, 2014 | 51 | 2014 |
| Efficient construction of connected dominating set in wireless ad hoc networks B Han, HH Fu, L Lin, W Jia 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE …, 2004 | 48 | 2004 |
| Mic-svm: Designing a highly efficient support vector machine for advanced modern multi-core and many-core architectures Y You, SL Song, H Fu, A Marquez, MM Dehnavi, K Barker, KW Cameron, ... 2014 IEEE 28th International Parallel and Distributed Processing Symposium …, 2014 | 46 | 2014 |
| swdnn: A library for accelerating deep learning applications on sunway taihulight J Fang, H Fu, W Zhao, B Chen, W Zheng, G Yang 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2017 | 44 | 2017 |
| Large-scale oil palm tree detection from high-resolution satellite images using two-stage convolutional neural networks W Li, R Dong, H Fu, L Yu Remote Sensing 11 (1), 11, 2019 | 43 | 2019 |
| FPGA designs with optimized logarithmic arithmetic H Fu, O Mencer, W Luk IEEE Transactions on Computers 59 (7), 1000-1006, 2010 | 43 | 2010 |
