Cracks identification using mask region-based denoised deformable convolutional network

HIGHLIGHTS

  • who: Kia Wei Kee from the Curtin University Malaysia, CDT, Miri, Malaysia have published the research work: Cracks identification using mask region-based denoised deformable convolutional network, in the Journal: (JOURNAL)
  • what: In this paper a Region-based Network (R-DDCN) is proposed to detect for accurate instance segmentation and image classification. convolution is introduced to improve the modeling capability of convolution layer.
  • how: This result showed that the loss incurred during the training process of the 600 training dataset for mask R-DDCN is acceptable if not equal to the original and . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?