Transfer Learning Based Evolutionary Algorithm for Composite Face Sketch Recognition

Author(s):  
Tarang Chugh ◽  
Maneet Singh ◽  
Shruti Nagpal ◽  
Richa Singh ◽  
Mayank Vatsa
Author(s):  
Heydi Mendez-Vazquez ◽  
Fabiola Becerra-Riera ◽  
Annette Morales-Gonzalez ◽  
Leyanis Lopez-Avila ◽  
Massimo Tistarelli

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Liang Fan ◽  
Xianfang Sun ◽  
Paul L. Rosin

2018 ◽  
Vol 11 (3) ◽  
pp. 541-548
Author(s):  
Abdul Rahman ◽  
Mirza Mohammed Sufyan Beg

2018 ◽  
Vol 21 ◽  
pp. 00008
Author(s):  
Mateusz Tybura

The key role of cryptography is to make cipher so hard to reproduce without knowing all the details that no one besides the recipient could decipher the message. Those algorithms which are used nowadays gets its security mostly from highly reliable algorithms and/or complicated cryptographic keys. Unfortunately, those human-made methods aren‘t invulnerable so sooner or later they compromise. So, it could be really useful to make a cipher which could change. But currently only neural networks are capable of thing known as transfer learning. In this article similar method was proposed in order to make it possible to re-learn already established evolutionary algorithm to do new, similar task.


Sign in / Sign up

Export Citation Format

Share Document