141 citations · 766 across the 81 of their papers we have counts for
13 papers · 1 filter
Neural-based Compression Scheme for Solar Image Data
Ali Zafari, Atefeh Khoshkhahtinat, Jeremy A. Grajeda +6
Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them eff…
Multi-spectral Entropy Constrained Neural Compression of Solar Imagery
Ali Zafari, Atefeh Khoshkhahtinat, Piyush M. Mehta +4
Missions studying the dynamic behaviour of the Sun are defined to capture multi-spectral images of the sun and transmit them to the ground station in a daily basis. To make transmi…
Trading-off Mutual Information on Feature Aggregation for Face Recognition
Mohammad Akyash, Ali Zafari, Nasser M. Nasrabadi
Despite the advances in the field of Face Recognition (FR), the precision of these methods is not yet sufficient. To improve the FR performance, this paper proposes a technique to…
Multi-Context Dual Hyper-Prior Neural Image Compression
Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta +3
Transform and entropy models are the two core components in deep image compression neural networks. Most existing learning-based image compression methods utilize convolutional-bas…
Context-Aware Neural Video Compression on Solar Dynamics Observatory
Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta +4
NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes of the Sun's daily activity. Data compression is crucial for space missions to reduce data storage and v…
Towards Generalizable Morph Attack Detection with Consistency Regularization
Hossein Kashiani, Niloufar Alipour Talemi, Mohammad Saeed Ebrahimi Saadabadi +1
Though recent studies have made significant progress in morph attack detection by virtue of deep neural networks, they often fail to generalize well to unseen morph attacks. With n…
Deep Boosting Multi-Modal Ensemble Face Recognition with Sample-Level Weighting
Sahar Rahimi Malakshan, Mohammad Saeed Ebrahimi Saadabadi, Nima Najafzadeh +1
Deep convolutional neural networks have achieved remarkable success in face recognition (FR), partly due to the abundant data availability. However, the current training benchmarks…
CCFace: Classification Consistency for Low-Resolution Face Recognition
Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Hossein Kashiani +1
In recent years, deep face recognition methods have demonstrated impressive results on in-the-wild datasets. However, these methods have shown a significant decline in performance…
AAFACE: Attribute-aware Attentional Network for Face Recognition
Niloufar Alipour Talemi, Hossein Kashiani, Sahar Rahimi Malakshan +4
In this paper, we present a new multi-branch neural network that simultaneously performs soft biometric (SB) prediction as an auxiliary modality and face recognition (FR) as the ma…
Improving Face Recognition from Caption Supervision with Multi-Granular Contextual Feature Aggregation
Md Mahedi Hasan, Nasser Nasrabadi
We introduce caption-guided face recognition (CGFR) as a new framework to improve the performance of commercial-off-the-shelf (COTS) face recognition (FR) systems. In contrast to c…
Frequency Disentangled Features in Neural Image Compression
Ali Zafari, Atefeh Khoshkhahtinat, Piyush Mehta +3
The design of a neural image compression network is governed by how well the entropy model matches the true distribution of the latent code. Apart from the model capacity, this abi…
A Quality Aware Sample-to-Sample Comparison for Face Recognition
Mohammad Saeed Ebrahimi Saadabadi, Sahar Rahimi Malakshan, Ali Zafari +2
Currently available face datasets mainly consist of a large number of high-quality and a small number of low-quality samples. As a result, a Face Recognition (FR) network fails to…
Deep Transductive Transfer Learning for Automatic Target Recognition
Shoaib M. Sami, Nasser M. Nasrabadi, Raghuveer Rao
One of the major obstacles in designing an automatic target recognition (ATR) algorithm, is that there are often labeled images in one domain (i.e., infrared source domain) but no…