A5016946378- Remote-Sensing Image Classification
- Remote Sensing in Agriculture
- Advanced Image Fusion Techniques
- Remote Sensing and LiDAR Applications
- Remote Sensing and Land Use
- Biometric Identification and Security
- Gait Recognition and Analysis
- Image Retrieval and Classification Techniques
- User Authentication and Security Systems
- Advanced Image and Video Retrieval Techniques
Northeast Forestry University
2015-2024
The spatiotemporal remote sensing images have a significant importance in forest ecological monitoring, carbon management, and other related fields. Spatiotemporal data fusion technology of combines high temporal resolution to address the current limitation single sensors obtaining resolution. This has gained widespread attention recent years. However, models still exhibit some shortcomings dealing with land cover changes, such as poor clustering results, inaccurate incremental calculations,...
Forest canopy closure is an important parameter to study forest ecosystem and understand the status of resources. With development remote sensing big data, amount data has increased sharply, which makes existing serial processing face severe challenges.In order satisfy requirements efficient processing, Spark open source framework applied parallel images, a density inversion algorithm based on proposed. We call this Sparkpr. Based GF-1 images 80 actual measured sample points obtained by...
Through the in-depth study on existing fingerprint identification technologies, combined with actual characteristics of embedded system, this paper improves algorithm, reducing time complexity matching algorithm. The experimental results show that algorithm proposed in can perfectly meet requirements therefore has high practical value.