Improving the classification accuracy of fishes and invertebrates using residual convolutional neural networks

HIGHLIGHTS

• who: X. Yang and colleagues from the School of Computer Science and Technology, Zhejiang Sci-Tech University, Xuelin Street, Jianggan District, Hangzhou, Zhejiang, China have published the article: Improving the classification accuracy of fishes and invertebrates using residual convolutional neural networks, in the Journal: (JOURNAL) of February/14,/2023
• what: The authors make the following contributions in this paper: Aiming at improving the performance in this context, the authors propose a classification algorithm model combining Resnet50 and an enhancement of the error-minimization random vector functional link (EEMRVFL). This study compares the classification accuracy of . . .
  

   

  

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

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

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