From local to global: class feature fused fully convolutional network for hyperspectral image classification

HIGHLIGHTS

• who: Qian Liu et al. from the School of Computer Science and Engineering, Nanjing University of Science and Technology have published the paper: From Local to Global: Class Feature Fused Fully Convolutional Network for Hyperspectral Image Classification, in the Journal: (JOURNAL)
• what: To address the above issues the authors propose a class feature fused fully convolutional network (CFF-FCN) with a local feature extraction block (LFEB) and a class feature fusion block (CFFB) to jointly utilize local and global information. The authors design a deep FCN classification framework to capture contextual information with more efficient . . .
  

   

  

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