Farhad is a researcher in VisTeam and a PhD student at Instituto Universitário de Lisboa and Faculty of Science of the University of Lisbon. He is researching in area of Natural Language processing and deep learning to modelling News and Tweets for the market. He studied advance statistical physics in bachelor and in master, He studied complex system at department of Physics.
Related Content
StylePuncher: encoding a hidden QR code into images
Featured in: 14th International Conference on Pattern Recognition Applications and Methods (ICPRAM'25)
Young Labeled Faces in the Wild (YLFW): A Dataset for Children Faces Recognition
Authors: Iurii Medveved, Farhad Shadmand and Nuno Gonçalves
Date:2024
Featured in: 2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG)
StampOne: Addressing Frequency Balance in Printer-proof Steganography
Authors: Farhad Shadmand, Iurii Medvedev, Luiz Schirmer, João Marcos and Nuno Gonçalves
Date:2024
Featured in: IEEE/CVF Conference on Computer Vision and Pattern Recognition
MorDeephy: Face Morphing Detection via Fused Classification
Authors: Iurii Medvedev, Farhad Shadmand and Nuno Gonçalves
Date:2023
Featured in: 12th International Conference on Pattern Recognition Application and Methods, Lisbon, Portugal.
Steganography Applications of StyleGAN: A Short Analytical Investigation from Hiding Message in Face Image
Authors: Farhad Shadmand, Luiz Schirmer and Nuno Gonçalves
Date:2023
Towards Facial Biometrics for ID Document Validation in Mobile Devices
Authors: Iurii Medvedev, Farhad Shadmand, Leandro Cruz and Nuno Gonçalves
Date:2021
Featured in: Applied Sciences, 2021
CodeFace: a deep learning printer-proofsteganography for Face Portraits
Authors: Farhad Shadmand, Iurii Medvedev and Nuno Gonçalves
Date:2021
Featured in: IEEE Access, 2021
Systems for encoding, decoding and validing the integrity of a security document with a steeganography encoded image and methods, security document, computer devices, computer programs and associated reading media
Authors: Nuno Gonçalves and Farhad Shadmand
Date:2021
Featured in: Applicants: Imprensa Nacional-Casa da Moeda and University of Coimbra
RiemStega: Covariance-based loss for print-proof transmission of data in images
