Search Results for author: Nasser M. Nasrabadi

Found 67 papers, 9 papers with code

Transporting Labels via Hierarchical Optimal Transport for Semi-Supervised Learning

no code implementations ECCV 2020 Fariborz Taherkhani, Ali Dabouei, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

Semi-Supervised Learning (SSL) based on Convolutional Neural Networks (CNNs) have recently been proven as powerful tools for standard tasks such as image classification when there is not a sufficient amount of labeled data available during the training.

Image Classification

Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning

no code implementations18 Oct 2021 Uche Osahor, Nasser M. Nasrabadi

In few-shot classification, the primary goal is to learn representations from a few samples that generalize well for novel classes.

Data Augmentation Few-Shot Learning

Deep adversarial attack on target detection systems

no code implementations12 Aug 2021 Uche M. Osahor, Nasser M. Nasrabadi

Target detection systems identify targets by localizing their coordinates on the input image of interest.

Adversarial Attack

Deep GAN-Based Cross-Spectral Cross-Resolution Iris Recognition

no code implementations3 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.

Iris Recognition

Tasks Structure Regularization in Multi-Task Learning for Improving Facial Attribute Prediction

no code implementations29 Jul 2021 Fariborz Taherkhani, Ali Dabouei, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

To address this problem, we use a new Multi-Task Learning (MTL) paradigm in which a facial attribute predictor uses the knowledge of other related attributes to obtain a better generalization performance.

Multi-Task Learning

Attention Aware Wavelet-based Detection of Morphed Face Images

no code implementations29 Jun 2021 Poorya Aghdaie, Baaria Chaudhary, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

Morphed images have exploited loopholes in the face recognition checkpoints, e. g., Credential Authentication Technology (CAT), used by Transportation Security Administration (TSA), which is a non-trivial security concern.

Face Recognition

Differential Morph Face Detection using Discriminative Wavelet Sub-bands

no code implementations24 Jun 2021 Baaria Chaudhary, Poorya Aghdaie, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

For some of the sub-bands, there is a marked difference between the entropy of the sub-band in a bona fide image and the identical sub-band's entropy in a morphed image.

Face Detection Face Recognition

FDeblur-GAN: Fingerprint Deblurring using Generative Adversarial Network

no code implementations21 Jun 2021 Amol S. Joshi, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi

It is added to generate ridge maps to ensure that fingerprint information and minutiae are preserved in the deblurring process and prevent the model from generating erroneous minutiae.

Deblurring

Self-Supervised Wasserstein Pseudo-Labeling for Semi-Supervised Image Classification

no code implementations CVPR 2021 Fariborz Taherkhani, Ali Dabouei, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

The goal is to use Wasserstein metric to provide pseudo labels for the unlabeled images to train a Convolutional Neural Networks (CNN) in a Semi-Supervised Learning (SSL) manner for the classification task.

Classification Self-Supervised Learning +1

Detection of Morphed Face Images Using Discriminative Wavelet Sub-bands

no code implementations16 Jun 2021 Poorya Aghdaie, Baaria Chaudhary, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

To detect morphing attacks, we propose a method which is based on a discriminative 2D Discrete Wavelet Transform (2D-DWT).

Face Recognition

HGAN: Hybrid Generative Adversarial Network

no code implementations7 Feb 2021 Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi

However, GANs overlook the explicit data density characteristics which leads to undesirable quantitative evaluations and mode collapse.

Density Estimation

A Large-Scale, Time-Synchronized Visible and Thermal Face Dataset

no code implementations7 Jan 2021 Domenick Poster, Matthew Thielke, Robert Nguyen, Srinivasan Rajaraman, Xing Di, Cedric Nimpa Fondje, Vishal M. Patel, Nathaniel J. Short, Benjamin S. Riggan, Nasser M. Nasrabadi, Shuowen Hu

Thermal face imagery, which captures the naturally emitted heat from the face, is limited in availability compared to face imagery in the visible spectrum.

Face Verification

Matching Distributions via Optimal Transport for Semi-Supervised Learning

no code implementations4 Dec 2020 Fariborz Taherkhani, Hadi Kazemi, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi

Semi-Supervised Learning (SSL) approaches have been an influential framework for the usage of unlabeled data when there is not a sufficient amount of labeled data available over the course of training.

Image Classification

Differential Morphed Face Detection Using Deep Siamese Networks

no code implementations2 Dec 2020 Sobhan Soleymani, Baaria Chaudhary, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi

Although biometric facial recognition systems are fast becoming part of security applications, these systems are still vulnerable to morphing attacks, in which a facial reference image can be verified as two or more separate identities.

Decision Making Face Detection

Mutual Information Maximization on Disentangled Representations for Differential Morph Detection

no code implementations2 Dec 2020 Sobhan Soleymani, Ali Dabouei, Fariborz Taherkhani, Jeremy Dawson, Nasser M. Nasrabadi

The network is trained by triplets of face images, in which the intermediate image inherits the landmarks from one image and the appearance from the other image.

Cross-Spectral Iris Matching Using Conditional Coupled GAN

no code implementations9 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.

Iris Recognition

Attribute Adaptive Margin Softmax Loss using Privileged Information

no code implementations4 Sep 2020 Seyed Mehdi Iranmanesh, Ali Dabouei, Nasser M. Nasrabadi

We present a novel framework to exploit privileged information for recognition which is provided only during the training phase.

Face Recognition Person Re-Identification

Efficient OCT Image Segmentation Using Neural Architecture Search

no code implementations28 Jul 2020 Saba Heidari Gheshlaghi, Omid Dehzangi, Ali Dabouei, Annahita Amireskandari, Ali Rezai, Nasser M. Nasrabadi

We incorporate the Unet architecture in the NAS framework as its backbone for the segmentation of the retinal layers in our collected and pre-processed OCT image dataset.

Neural Architecture Search Semantic Segmentation +1

Joint-SRVDNet: Joint Super Resolution and Vehicle Detection Network

no code implementations3 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.

Super-Resolution

PF-cpGAN: Profile to Frontal Coupled GAN for Face Recognition in the Wild

no code implementations25 Apr 2020 Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson, Matthew C. Valenti, Nasser M. Nasrabadi

In this paper, we hypothesize that the profile face domain possesses a gradual connection with the frontal face domain in the deep feature space.

Face Recognition

Error-Corrected Margin-Based Deep Cross-Modal Hashing for Facial Image Retrieval

no code implementations3 Apr 2020 Fariborz Taherkhani, Veeru Talreja, Matthew C. Valenti, Nasser M. Nasrabadi

The DNDCMH network consists of two separatecomponents: an attribute-based deep cross-modal hashing (ADCMH) module, which uses a margin (m)-based loss function toefficiently learn compact binary codes to preserve similarity between modalities in the Hamming space, and a neural error correctingdecoder (NECD), which is an error correcting decoder implemented with a neural network.

Face Image Retrieval

SuperMix: Supervising the Mixing Data Augmentation

1 code implementation CVPR 2021 Ali Dabouei, Sobhan Soleymani, Fariborz Taherkhani, Nasser M. Nasrabadi

In this paper, we propose a supervised mixing augmentation method, termed SuperMix, which exploits the knowledge of a teacher to mix images based on their salient regions.

Data Augmentation General Classification +2

Boosting Deep Face Recognition via Disentangling Appearance and Geometry

no code implementations13 Jan 2020 Ali Dabouei, Fariborz Taherkhani, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

We demonstrate that the proposed approach enhances the performance of deep face recognition models by assisting the training process in two ways.

Face Recognition Transfer Learning

Identity-Aware Deep Face Hallucination via Adversarial Face Verification

no code implementations17 Sep 2019 Hadi Kazemi, Fariborz Taherkhani, Nasser M. Nasrabadi

First, we propose a multi-scale generator architecture for face hallucination with a high up-scaling ratio factor, which has multiple intermediate outputs at different resolutions.

Face Hallucination Face Verification

Deep Sparse Band Selection for Hyperspectral Face Recognition

no code implementations15 Aug 2019 Fariborz Taherkhani, Jeremy Dawson, Nasser M. Nasrabadi

In this book chapter, we propose a new Convolutional Neural Network (CNN) framework which adopts a structural sparsity learning technique to select the optimal spectral bands to obtain the best face recognition performance over all of the spectral bands.

Face Recognition

Attribute-Guided Coupled GAN for Cross-Resolution Face Recognition

no code implementations5 Aug 2019 Veeru Talreja, Fariborz Taherkhani, Matthew C. Valenti, Nasser M. Nasrabadi

In this paper, we propose a novel attribute-guided cross-resolution (low-resolution to high-resolution) face recognition framework that leverages a coupled generative adversarial network (GAN) structure with adversarial training to find the hidden relationship between the low-resolution and high-resolution images in a latent common embedding subspace.

Face Recognition

Zero-Shot Deep Hashing and Neural Network Based Error Correction for Face Template Protection

no code implementations5 Aug 2019 Veeru Talreja, Matthew C. Valenti, Nasser M. Nasrabadi

The proposed architecture consists of two major components: a deep hashing (DH) component, which is used for robust mapping of face images to their corresponding intermediate binary codes, and a NND component, which corrects errors in the intermediate binary codes that are caused by differences in the enrollment and probe biometrics due to factors such as variation in pose, illumination, and other factors.

Attribute-Guided Deep Polarimetric Thermal-to-visible Face Recognition

no code implementations27 Jul 2019 Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi

In this paper, we present an attribute-guided deep coupled learning framework to address the problem of matching polarimetric thermal face photos against a gallery of visible faces.

Face Recognition

Adversarial Examples to Fool Iris Recognition Systems

no code implementations21 Jun 2019 Sobhan Soleymani, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi

Therefore, to compensate for this shortcoming, we propose to train a deep auto-encoder surrogate network to mimic the conventional iris code generation procedure.

Code Generation Iris Recognition

Using Deep Cross Modal Hashing and Error Correcting Codes for Improving the Efficiency of Attribute Guided Facial Image Retrieval

no code implementations11 Feb 2019 Veeru Talreja, Fariborz Taherkhani, Matthew C. Valenti, Nasser M. Nasrabadi

With benefits of fast query speed and low storage cost, hashing-based image retrieval approaches have garnered considerable attention from the research community.

Face Image Retrieval

Learning to Authenticate with Deep Multibiometric Hashing and Neural Network Decoding

no code implementations11 Feb 2019 Veeru Talreja, Sobhan Soleymani, Matthew C. Valenti, Nasser M. Nasrabadi

The MDHND consists of two separate modules: a multimodal deep hashing (MDH) module, which is used for feature-level fusion and binarization of multiple biometrics, and a neural network decoder (NND) module, which is used to refine the intermediate binary codes generated by the MDH and compensate for the difference between enrollment and probe biometrics (variations in pose, illumination, etc.).

Binarization

Style and Content Disentanglement in Generative Adversarial Networks

no code implementations14 Nov 2018 Hadi Kazemi, Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi

This paper describes the Style and Content Disentangled GAN (SC-GAN), a new unsupervised algorithm for training GANs that learns disentangled style and content representations of the data.

Image Generation

Unsupervised Facial Geometry Learning for Sketch to Photo Synthesis

no code implementations12 Oct 2018 Hadi Kazemi, Fariborz Taherkhani, Nasser M. Nasrabadi

In contrast to current unsupervised image-to-image translation techniques, our framework leverages a novel perceptual discriminator to learn the geometry of human face.

Translation Unsupervised Image-To-Image Translation

Fast Geometrically-Perturbed Adversarial Faces

1 code implementation24 Sep 2018 Ali Dabouei, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi

The state-of-the-art performance of deep learning algorithms has led to a considerable increase in the utilization of machine learning in security-sensitive and critical applications.

Face Recognition

Convolutional Neural Networks for Aerial Vehicle Detection and Recognition

no code implementations26 Aug 2018 Amir Soleimani, Nasser M. Nasrabadi, Elias Griffith, Jason Ralph, Simon Maskell

This paper investigates the problem of aerial vehicle recognition using a text-guided deep convolutional neural network classifier.

Deep Sketch-Photo Face Recognition Assisted by Facial Attributes

no code implementations31 Jul 2018 Seyed Mehdi Iranmanesh, Hadi Kazemi, Sobhan Soleymani, Ali Dabouei, Nasser M. Nasrabadi

The proposed Attribute-Assisted Deep Con- volutional Neural Network (AADCNN) method exploits the facial attributes and leverages the loss functions from the facial attributes identification and face verification tasks in order to learn rich discriminative features in a common em- bedding subspace.

Face Recognition Face Verification

ID Preserving Generative Adversarial Network for Partial Latent Fingerprint Reconstruction

no code implementations31 Jul 2018 Ali Dabouei, Sobhan Soleymani, Hadi Kazemi, Seyed Mehdi Iranmanesh, Jeremy Dawson, Nasser M. Nasrabadi

We achieved the rank-10 accuracy of 88. 02\% on the IIIT-Delhi latent fingerprint database for the task of latent-to-latent matching and rank-50 accuracy of 70. 89\% on the IIIT-Delhi MOLF database for the task of latent-to-sensor matching.

Convolutional Neural Networks for Aerial Multi-Label Pedestrian Detection

no code implementations16 Jul 2018 Amir Soleimani, Nasser M. Nasrabadi

The low resolution of objects of interest in aerial images makes pedestrian detection and action detection extremely challenging tasks.

Action Detection Pedestrian Detection +1

Generalized Bilinear Deep Convolutional Neural Networks for Multimodal Biometric Identification

no code implementations3 Jul 2018 Sobhan Soleymani, Amirsina Torfi, Jeremy Dawson, Nasser M. Nasrabadi

We demonstrate that, rather than spatial fusion at the convolutional layers, the fusion can be performed on the outputs of the fully-connected layers of the modality-specific CNNs without any loss of performance and with significant reduction in the number of parameters.

Person Identification

Multi-Level Feature Abstraction from Convolutional Neural Networks for Multimodal Biometric Identification

no code implementations3 Jul 2018 Sobhan Soleymani, Ali Dabouei, Hadi Kazemi, Jeremy Dawson, Nasser M. Nasrabadi

Multiple features are extracted at several different convolutional layers from each modality-specific CNN for joint feature fusion, optimization, and classification.

General Classification Person Identification

A Deep Face Identification Network Enhanced by Facial Attributes Prediction

no code implementations20 Apr 2018 Fariborz Taherkhani, Nasser M. Nasrabadi, Jeremy Dawson

In this paper, we propose a new deep framework which predicts facial attributes and leverage it as a soft modality to improve face identification performance.

Face Identification Gender Prediction

Attribute-Centered Loss for Soft-Biometrics Guided Face Sketch-Photo Recognition

no code implementations9 Apr 2018 Hadi Kazemi, Sobhan Soleymani, Ali Dabouei, Mehdi Iranmanesh, Nasser M. Nasrabadi

Specifically, an attribute-centered loss is proposed which learns several distinct centers, in a shared embedding space, for photos and sketches with different combinations of attributes.

Attention-Based Guided Structured Sparsity of Deep Neural Networks

1 code implementation13 Feb 2018 Amirsina Torfi, Rouzbeh A. Shirvani, Sobhan Soleymani, Nasser M. Nasrabadi

Network pruning is aimed at imposing sparsity in a neural network architecture by increasing the portion of zero-valued weights for reducing its size regarding energy-efficiency consideration and increasing evaluation speed.

Network Pruning

Deep Cross Polarimetric Thermal-to-visible Face Recognition

no code implementations4 Jan 2018 Seyed Mehdi Iranmanesh, Ali Dabouei, Hadi Kazemi, Nasser M. Nasrabadi

we propose a coupled deep neural network architecture which leverages relatively large visible and thermal datasets to overcome the problem of overfitting and eventually we train it by a polarimetric thermal face dataset which is the first of its kind.

Face Recognition

Fingerprint Distortion Rectification using Deep Convolutional Neural Networks

no code implementations3 Jan 2018 Ali Dabouei, Hadi Kazemi, Seyed Mehdi Iranmanesh, Jeremi Dawson, Nasser M. Nasrabadi

Elastic distortion of fingerprints has a negative effect on the performance of fingerprint recognition systems.

Rectification

An Order Preserving Bilinear Model for Person Detection in Multi-Modal Data

1 code implementation20 Dec 2017 Oytun Ulutan, Benjamin S. Riggan, Nasser M. Nasrabadi, B. S. Manjunath

We propose a new order preserving bilinear framework that exploits low-resolution video for person detection in a multi-modal setting using deep neural networks.

Human Detection

Multibiometric Secure System Based on Deep Learning

no code implementations7 Aug 2017 Veeru Talreja, Matthew C. Valenti, Nasser M. Nasrabadi

In this paper, we propose a secure multibiometric system that uses deep neural networks and error-correction coding.

3D Convolutional Neural Networks for Cross Audio-Visual Matching Recognition

2 code implementations18 Jun 2017 Amirsina Torfi, Seyed Mehdi Iranmanesh, Nasser M. Nasrabadi, Jeremy Dawson

We propose the use of a coupled 3D Convolutional Neural Network (3D-CNN) architecture that can map both modalities into a representation space to evaluate the correspondence of audio-visual streams using the learned multimodal features.

Speaker Verification Speech Recognition

Text-Independent Speaker Verification Using 3D Convolutional Neural Networks

6 code implementations26 May 2017 Amirsina Torfi, Jeremy Dawson, Nasser M. Nasrabadi

In our paper, we propose an adaptive feature learning by utilizing the 3D-CNNs for direct speaker model creation in which, for both development and enrollment phases, an identical number of spoken utterances per speaker is fed to the network for representing the speakers' utterances and creation of the speaker model.

Text-Independent Speaker Verification

Supervised Deep Sparse Coding Networks

1 code implementation29 Jan 2017 Xiaoxia Sun, Nasser M. Nasrabadi, Trac. D. Tran

In this paper, we describe the deep sparse coding network (SCN), a novel deep network that encodes intermediate representations with nonnegative sparse coding.

General Classification

Sparse Coding with Fast Image Alignment via Large Displacement Optical Flow

no code implementations21 Dec 2015 Xiaoxia Sun, Nasser M. Nasrabadi, Trac. D. Tran

Sparse representation-based classifiers have shown outstanding accuracy and robustness in image classification tasks even with the presence of intense noise and occlusion.

Dictionary Learning Image Classification +1

Learning to classify with possible sensor failures

no code implementations16 Jul 2015 Tianpei Xie, Nasser M. Nasrabadi, Alfred O. Hero

In this paper, we propose a general framework to learn a robust large-margin binary classifier when corrupt measurements, called anomalies, caused by sensor failure might be present in the training set.

Anomaly Detection Classification +2

Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification

no code implementations10 Feb 2015 Soheil Bahrampour, Nasser M. Nasrabadi, Asok Ray, Kenneth W. Jenkins

In this paper, we propose a supervised dictionary learning algorithm in the kernel domain for hyperspectral image classification.

Classification Dictionary Learning +2

Multimodal Task-Driven Dictionary Learning for Image Classification

1 code implementation4 Feb 2015 Soheil Bahrampour, Nasser M. Nasrabadi, Asok Ray, W. Kenneth Jenkins

Dictionary learning algorithms have been successfully used for both reconstructive and discriminative tasks, where an input signal is represented with a sparse linear combination of dictionary atoms.

Action Recognition Classification +4

Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints

no code implementations3 Feb 2015 Xiaoxia Sun, Nasser M. Nasrabadi, Trac. D. Tran

We propose to enforce structured sparsity priors on the task-driven dictionary learning method in order to improve the performance of the hyperspectral classification.

Dictionary Learning General Classification +1

Collaborative Multi-sensor Classification via Sparsity-based Representation

no code implementations29 Oct 2014 Minh Dao, Nam H. Nguyen, Nasser M. Nasrabadi, Trac. D. Tran

In this paper, we propose a general collaborative sparse representation framework for multi-sensor classification, which takes into account the correlations as well as complementary information between heterogeneous sensors simultaneously while considering joint sparsity within each sensor's observations.

Classification General Classification

Quality-based Multimodal Classification Using Tree-Structured Sparsity

no code implementations CVPR 2014 Soheil Bahrampour, Asok Ray, Nasser M. Nasrabadi, Kenneth W. Jenkins

An accelerated proximal algorithm is proposed to solve the optimization problem, which is an efficient tool for feature-level fusion among either homogeneous or heterogeneous sources of information.

Classification Face Recognition +1

Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification

no code implementations16 Jan 2014 Xiaoxia Sun, Qing Qu, Nasser M. Nasrabadi, Trac. D. Tran

Pixel-wise classification, where each pixel is assigned to a predefined class, is one of the most important procedures in hyperspectral image (HSI) analysis.

Classification General Classification +1

Robust Lasso with missing and grossly corrupted observations

no code implementations NeurIPS 2011 Nasser M. Nasrabadi, Trac. D. Tran, Nam Nguyen

Our second set of results applies to a general class of Gaussian design matrix $X$ with i. i. d rows $\oper N(0, \Sigma)$, for which we provide a surprising phenomenon: the extended Lasso can recover exact signed supports of both $\beta^{\star}$ and $e^{\star}$ from only $\Omega(k \log p \log n)$ observations, even the fraction of corruption is arbitrarily close to one.

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