MULS-Net: A Multilevel Supervised Network for Ship Tracking From Low-Resolution Remote-Sensing Image Sequences.
Yuan LiQizhi XuZiyang KongWei LiPublished in: IEEE Trans. Geosci. Remote. Sens. (2023)
Keyphrases
- remote sensing
- high resolution
- low resolution
- image sequences
- super resolution
- change detection
- multispectral
- satellite images
- remote sensing images
- high frequency
- motion analysis
- high spatial resolution
- spatial resolution
- object tracking
- low resolution images
- image fusion
- satellite imagery
- high quality
- land cover
- depth map
- hyperspectral
- image processing
- unsupervised learning
- motion segmentation
- machine learning
- video sequences
- hyperspectral images
- image frames
- motion estimation
- multi frame
- computer vision
- hyperspectral imagery
- semi supervised
- particle filter
- kalman filter
- motion model
- feature selection
- optical flow
- image analysis
- sparse representation
- infrared
- three dimensional