FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding

Nov-20-2025, 06:36:38 GMT–Neural Information Processing Systems

Fine urban change segmentation using multi-temporal remote sensing images is essential for understanding human-environment interactions in urban areas.

artificial intelligence, deep learning, machine learning, (18 more...)

Neural Information Processing Systems

Nov-20-2025, 06:36:38 GMT

Conferences PDF

Country:
- Asia > China
  - Guangdong Province > Shenzhen (0.04)
  - Hong Kong (0.04)
  - Shaanxi Province > Xi'an (0.06)
- Europe > Germany
  - Brandenburg > Potsdam (0.04)
- North America > United States (0.14)

Genre:
- Research Report (0.46)

Industry:
- Energy > Renewable
  - Geothermal > Geothermal Energy Exploration and Development > Geophysical Analysis & Survey (0.37)
- Law > Real Estate Law (0.43)

Technology:
- Information Technology > Artificial Intelligence
  - Machine Learning > Neural Networks
    - Deep Learning (0.46)
  - Representation & Reasoning (0.93)
  - Vision (1.00)

Duplicate Docs Excel Report

Title
FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding

Similar Docs Excel Report more

Title	Similarity	Source
None found