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Found 3 papers, 3 papers with code
SSG2: A new modelling paradigm for semantic segmentation
By adding this "temporal" dimension, we exploit strong signal correlations between successive observations in the sequence to reduce error rates.
Looking for change? Roll the Dice and demand Attention
Further, we introduce a new encoder/decoder scheme, a network macro-topology, that is tailored for the task of change detection.
Building change detection for remote sensing images
Change Detection
+1
ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data
Scene understanding of high resolution aerial images is of great importance for the task of automated monitoring in various remote sensing applications.
