Classification of building damage using a novel convolutional neural network based on post-disaster aerial images

HIGHLIGHTS

• who: Zhonghua Hong and collaborators from the College of Information Technology, Shanghai Ocean University, Shanghai, China have published the Article: Classification of Building Damage Using a Novel Convolutional Neural Network Based on Post-Disaster Aerial Images, in the Journal: Sensors 2022, 22, xVGG-OR FOR PEER REVIEWL0 EBDC-Net of 28/06/2022
• what: To address the abovementioned issues, this study proposes a novel CNN-namely, the earthquake building damage classification net (EBDC-Net)-for assessment of building damage using post-disaster aerial images. The model was trained using the SGD optimizer;0.67 the . . .
  

   

  

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