A dual-branch deep learning architecture for multi-sensor and multi-temporal remote sensing semantic segmentation

HIGHLIGHTS

  • who: IEEE TRANSACTIONS ON GEOSCIENCE and colleagues from the (UNIVERSITY) have published the article: A Dual-Branch Deep Learning Architecture for Multi-Sensor and Multi-Temporal Remote Sensing Semantic Segmentation, in the Journal: (JOURNAL)
  • what: The authors propose a supervised Deep-Learning (DL) classification method that jointly performs a multi-scale and analysis of RS images acquired by different sensors. The authors propose a DL method for supervised classification that analyzes multi-sensor data with heterogeneous properties in spatial, spectral, and temporal resolutions. The authors design the two branches of the DL model to obtain . . .

     

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