no code implementations • 6 Jun 2023 • Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Ali Zafari, Moktari Mostofa, Nasser M. Nasrabadi
Our method adaptively finds and assigns more attention to the recognizable low-quality samples in the training datasets.
no code implementations • 15 Sep 2022 • Moktari Mostofa, Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Nasser M. Nasrabadi
Second, we develop a novel pose attention block (PAB) to specially guide the pose-agnostic feature extraction from profile faces.
no code implementations • 7 Sep 2022 • Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Sobhan Soleymani, Moktari Mostofa, Nasser M. Nasrabadi
In this paper, we seek to draw connections between the frontal and profile face images in an abstract embedding space.
no code implementations • 3 Aug 2021 • Moktari Mostofa, Salman Mohamadi, Jeremy Dawson, Nasser M. Nasrabadi
In the second approach, we design a coupled generative adversarial network (cpGAN) architecture consisting of a pair of cGAN modules that project the VIS and NIR iris images into a low-dimensional embedding domain to ensure maximum pairwise similarity between the feature vectors from the two iris modalities of the same subject.
no code implementations • 9 Oct 2020 • Moktari Mostofa, Fariborz Taherkhani, Jeremy Dawson, Nasser M. Nasrabadi
Cross-spectral iris recognition is emerging as a promising biometric approach to authenticating the identity of individuals.
no code implementations • 3 May 2020 • Moktari Mostofa, Syeda Nyma Ferdous, Benjamin S. Riggan, Nasser M. Nasrabadi
However, aerial vehicle detection on super-resolved images remains a challenging task due to the lack of discriminative information in the super-resolved images.