Weijia Li

Liweijia.jpg


Contact

Mail: liweijia621@gmail.com

Room: S-814, Meng MinWei Science Building Center for Earth System Science, Tsinghua University, Beijing, 100084

Current State

PhD Candidate in Department of Earth System Science, Tsinghua University

Experience

  • 2010 - 2014, Sun Yat-Sen University, Department of Computer Science, Bachelor
  • 2016 - 2017, Imperial College London, Department of Computing, Joint Ph.D. student
  • 2014 - Now, Tsinghua University, Department of Earth System Science, Ph.D. candidate

Research

My research interests include machine learning, high performance computing and remote sensing. I’m experienced in deep learning based remote sensing image understanding, especially in land cover classification, object detection and semantic segmentation. I am also interested in high performance computing for large-scale remote sensing data processing.

Publication

[1] Weijia Li, Haohuan Fu, Le Yu, and Arthur Cracknell. Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images. Remote Sensing, 9 (1), 22.

[2] Weijia Li, Haohuan Fu, Yang You, Le Yu, and Jiarui Fang. Parallel Multiclass Support Vector Machine for Remote Sensing Data Classification on Multicore and Many-Core Architectures. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017.

[3] Weijia Li, Haohuan Fu, Le Yu, Peng Gong, Duole Feng, Congcong Li, and Nicholas Clinton. Stacked Autoencoder-based deep learning for remote-sensing image classification: a case study of African land-cover mapping. International Journal of Remote Sensing, 37 (23), 5632-5646.

[4] Weijia Li, Conghui He, Jiarui Fang, and Haohuan Fu. Semantic Segmentation based Building Extraction Method using Multi-source GIS Map Datasets and Satellite Imagery. CVPR Workshop on DeepGlobe Satellite Challenge 2018 (CVPRW 2018).

[5] Weijia Li, Conghui He, Haohuan Fu and Wayne Luk. An FPGA-based tree crown detection approach for remote sensing images. 2017 International Conference on Field-Programmable Technology (FPT 2017).

[6] Weijia Li, Haohuan Fu, and Le Yu. Deep convolutional neural network based large-scale oil palm tree detection for high-resolution remote sensing images. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2017).

[7] Haohuan Fu, Conghui He, Wayne Luk, Weijia Li, and Guangwen Yang. A Nanosecond-level Hybrid Table Design for Financial Market Data Generators. The 25th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2017).

[8] Conghui He, Haohuan Fu, Wayne Luk, Weijia Li, and Guangwen Yang. Exploring the Potential of Reconfigurable Platforms for Order Book Update. The 27th IEEE International on Field-Programmable Logic and Applications (FPL 2017).