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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

SCU-Counting: A large-scale benchmark dataset for multi-class object counting

Published in Transportation Research Part C: Emerging Technologies, 2024

This paper proposes a spatiotemporal deep learning framework for citywide short-term crash risk prediction across multiple temporal resolutions, integrating historical crash data, traffic dynamics, and point-of-interest information.

Recommended citation: Wei, X.-Y., Zhang, L., Ma, H.-Y., & Zhang, X.-F. (2024). SCU-Counting: A large-scale benchmark dataset for multi-class object counting. Journal or Conference Name.
Download Paper | Download Slides | Download Bibtex

Multi-class Object Counting Network with Adaptive Class Alignment Loss for Remote Sensing Images

Published in IEEE Signal Processing Letters, 2025

The paper proposes ACA-MOCN, a well-designed multi-class object counting framework combining adaptive class alignment loss and a filtering feature pyramid network. The approach effectively addresses class imbalance and fine-grained feature fusion in remote sensing images.

Recommended citation: Z. Zhu, L. Zhang, H. -Y. Ma, X. -Y. Wei and Y. Zhang, "Multi-class Object Counting Network with Adaptive Class Alignment Loss for Remote Sensing Images. IEEE Signal Processing Letters.
Download Paper | Download Slides | Download Bibtex

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.