Image retrieval using convolutional autoencoder, infogan, and vision transformer unsupervised models

HIGHLIGHTS

• who: Eman S. Sabry et al. from the Department of Communications and Computers Engineering, Higher Institute of Engineering, El-Shorouk Academy, El-Shorouk City, EgyptDepartment of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh, Saudi have published the research: Image Retrieval using Convolutional Autoencoder, InfoGAN, and Vision Transformer Unsupervised Models, in the Journal: (JOURNAL)
• what: Using visual features extracted from each of the three suggested retrieval systems, the authors compare the performance of logo image retrieval. The aim is to create . . .
  

   

  

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