Lightweight image super-resolution based on re-parameterization and self-calibrated convolution

HIGHLIGHTS

• who: Re-Parameterization and collaborators from the School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, China have published the Article: Lightweight Image Super-Resolution Based on Re-Parameterization and Self-Calibrated Convolution, in the Journal: Computational Intelligence and Neuroscience of 26/09/2022
• what: To address the above problems the authors propose a novel lightweight image super-resolution network (RepSCN) based on and self-calibration Specifically to reduce the computational cost while capturing more high-frequency details the authors designed a distillation block (RepDB) and a distillation block (SCDB). Since . . .
  

   

  

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