Deep learning with self-supervision and uncertainty regularization to count fish in underwater images

HIGHLIGHTS

• who: Penny Tarling and colleagues from the GERMANY Autu00f2noma Barcelona, Barcelona, Spain have published the paper: Deep learning with self-supervision and uncertainty regularization to count fish in underwater images, in the Journal: PLOS ONE of 22/07/2021
• what: The authors demonstrate the generalisability of the proposed counting framework through testing it on a recent benchmark dataset of high-resolution annotated underwater images from varying habitats (DeepFish). From experiments on both contrasting datasets the authors demonstrate the network outperforms the few other deep learning models implemented for solving this task. Funding: This work has . . .
  

   

  

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