Sizhuo Li
Postdoc
Geography 2
Øster Voldgade 10
1350 København K
Primary fields of research
I work in the interdisciplinary field of deep learning and remote sensing and I am interested in applying advanced neural networks to popular remote sensing problems, including intelligent forest management and carbon stock estimation. Development and adaptation of deep learning methods are the main focuses of my studies.
Current research
An automatic and scalable tree inventory framework based on UNet, enabling individual crown segmentation, tree counting, and tree height estimation at the country scale.
Fields of interest
Deep learning, remote sensing
ID: 226574618
Most downloads
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120
downloads
Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
72
downloads
Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
41
downloads
More than one quarter of Africa's tree cover is found outside areas previously classified as forest
Research output: Contribution to journal › Journal article › Research › peer-review
Published