Generative adversarial network for global image-based local image to improve malware classification using convolutional neural network

HIGHLIGHTS

• who: Sejun Jang and collaborators from the Department of Multimedia Engineering, Dongguk University-Seoul, Seoul, Korea have published the research: Generative Adversarial Network for Global Image-Based Local Image to Improve Malware Classification Using Convolutional Neural Network, in the Journal: (JOURNAL)
• what: In Inthis this paper, paper, g𝑔f 𝑓,𝑖,i is the merged image obtained utilizing 𝐺f𝑓,𝑖,i and f𝑔,i𝑓,𝑖. In this paper, two methods, global image-based local feature visualization and global and local image merge, were proposed.
• how: This paper proposes a method that uses a generative adversarial network (GAN . . .
  

   

  

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

  Thanks :)

  Username or E-mail:

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