Search Results for author: Ali Etemad

Found 42 papers, 9 papers with code

Holistic Semi-Supervised Approaches for EEG Representation Learning

no code implementations24 Sep 2021 Guangyi Zhang, Ali Etemad

Recently, supervised methods, which often require substantial amounts of class labels, have achieved promising results for EEG representation learning.

EEG Emotion Recognition +1

Multi-View Video-Based 3D Hand Pose Estimation

1 code implementation24 Sep 2021 Leyla Khaleghi, Alireza Sepas Moghaddam, Joshua Marshall, Ali Etemad

Recent works have shown that videos or multi-view images carry rich information regarding the hand, allowing for the development of more robust HPE systems.

3D Hand Pose Estimation

Wearable-based Classification of Running Styles with Deep Learning

no code implementations1 Sep 2021 Setareh Rahimi Taghanaki, Michael Rainbow, Ali Etemad

To develop a system capable of classifying running styles using wearables, we collect a dataset from 10 healthy runners performing 8 different pre-defined running styles.

Classification

Spatiotemporal Contrastive Learning of Facial Expressions in Videos

no code implementations6 Aug 2021 Shuvendu Roy, Ali Etemad

Experiments are performed on the Oulu-CASIA dataset and the performance is compared to other works in FER.

Contrastive Learning Facial Expression Recognition

Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition

no code implementations28 Jul 2021 Guangyi Zhang, Ali Etemad

We evaluate our framework using both a stacked autoencoder and an attention-based recurrent autoencoder.

Deep Attention EEG +2

Multi-Perspective LSTM for Joint Visual Representation Learning

1 code implementation CVPR 2021 Alireza Sepas-Moghaddam, Fernando Pereira, Paulo Lobato Correia, Ali Etemad

We validate the performance of our proposed architecture in the context of two multi-perspective visual recognition tasks namely lip reading and face recognition.

Face Recognition Lip Reading +1

Distilling EEG Representations via Capsules for Affective Computing

no code implementations30 Apr 2021 Guangyi Zhang, Ali Etemad

Then, we employ the teacher network to learn the discriminative features embedded in capsules by adopting a lightweight model (student network) to mimic the teacher using the privileged knowledge.

EEG Knowledge Distillation

Oriented Bounding Boxes for Small and Freely Rotated Objects

no code implementations24 Apr 2021 Mohsen Zand, Ali Etemad, Michael Greenspan

A novel object detection method is presented that handles freely rotated objects of arbitrary sizes, including tiny objects as small as $2\times 2$ pixels.

Object Detection

Flow-based Autoregressive Structured Prediction of Human Motion

no code implementations9 Apr 2021 Mohsen Zand, Ali Etemad, Michael Greenspan

A new method is proposed for human motion predition by learning temporal and spatial dependencies in an end-to-end deep neural network.

motion prediction Structured Prediction

Teacher-Student Adversarial Depth Hallucination to Improve Face Recognition

1 code implementation ICCV 2021 Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan, Ali Etemad

Moreover, face recognition experiments demonstrate that our hallucinated depth along with the input RGB images boosts performance across various architectures when compared to a single RGB modality by average values of +1. 2%, +2. 6%, and +2. 6% for IIIT-D, EURECOM, and LFW datasets respectively.

Face Recognition

Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting

no code implementations6 Apr 2021 Yangzheng Wu, Mohsen Zand, Ali Etemad, Michael Greenspan

We propose a novel keypoint voting scheme based on intersecting spheres, that is more accurate than existing schemes and allows for a smaller set of more disperse keypoints.

Pose Estimation

Identity and Posture Recognition in Smart Beds with Deep Multitask Learning

no code implementations5 Apr 2021 Vandad Davoodnia, Ali Etemad

Sleep posture analysis is widely used for clinical patient monitoring and sleep studies.

Potential Impacts of Smart Homes on Human Behavior: A Reinforcement Learning Approach

no code implementations26 Feb 2021 Shashi Suman, Ali Etemad, Francois Rivest

We then investigate the possibility of human behavior being altered as a result of the smart home and the human model adapting to one-another.

Hierarchical Reinforcement Learning Q-Learning

Deep Gait Recognition: A Survey

no code implementations18 Feb 2021 Alireza Sepas-Moghaddam, Ali Etemad

Gait recognition is an appealing biometric modality which aims to identify individuals based on the way they walk.

Gait Recognition

CapsField: Light Field-based Face and Expression Recognition in the Wild using Capsule Routing

no code implementations10 Jan 2021 Alireza Sepas-Moghaddam, Ali Etemad, Fernando Pereira, Paulo Lobato Correia

A subset of the in the wild dataset contains facial images with different expressions, annotated for usage in the context of face expression recognition tests.

Depth as Attention for Face Representation Learning

1 code implementation3 Jan 2021 Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan, Ali Etemad

Our novel attention mechanism directs the deep network "where to look" for visual features in the RGB image by focusing the attention of the network using depth features extracted by a Convolution Neural Network (CNN).

Face Recognition Representation Learning

Detection of Maternal and Fetal Stress from the Electrocardiogram with Self-Supervised Representation Learning

1 code implementation3 Nov 2020 Pritam Sarkar, Silvia Lobmaier, Bibiana Fabre, Diego González, Alexander Mueller, Martin G. Frasch, Marta C. Antonelli, Ali Etemad

Our DL models accurately detect the chronic stress exposure group (AUROC=0. 982+/-0. 002), the individual psychological stress score (R2=0. 943+/-0. 009) and FSI at 34 weeks of gestation (R2=0. 946+/-0. 013), as well as the maternal hair cortisol at birth reflecting chronic stress exposure (0. 931+/-0. 006).

Representation Learning Self-Supervised Learning

Gait Recognition using Multi-Scale Partial Representation Transformation with Capsules

no code implementations18 Oct 2020 Alireza Sepas-Moghaddam, Saeed Ghorbani, Nikolaus F. Troje, Ali Etemad

In this context, we propose a novel deep network, learning to transfer multi-scale partial gait representations using capsules to obtain more discriminative gait features.

Gait Recognition

View-Invariant Gait Recognition with Attentive Recurrent Learning of Partial Representations

no code implementations18 Oct 2020 Alireza Sepas-Moghaddam, Ali Etemad

Our proposed model has been extensively tested on two large-scale CASIA-B and OU-MVLP gait datasets using four different test protocols and has been compared to a number of state-of-the-art and baseline solutions.

Gait Recognition

CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG

2 code implementations30 Sep 2020 Pritam Sarkar, Ali Etemad

Electrocardiogram (ECG) is the electrical measurement of cardiac activity, whereas Photoplethysmogram (PPG) is the optical measurement of volumetric changes in blood circulation.

Siamese Capsule Network for End-to-End Speaker Recognition In The Wild

no code implementations28 Sep 2020 Amirhossein Hajavi, Ali Etemad

Our model uses thin-ResNet for extracting speaker embeddings from utterances and a Siamese capsule network and dynamic routing as the Back-end to calculate a similarity score between the embeddings.

Speaker Recognition Speaker Verification

End-to-End Prediction of Parcel Delivery Time with Deep Learning for Smart-City Applications

no code implementations23 Sep 2020 Arthur Cruz de Araujo, Ali Etemad

The acquisition of massive data on parcel delivery motivates postal operators to foster the development of predictive systems to improve customer service.

FluentNet: End-to-End Detection of Speech Disfluency with Deep Learning

no code implementations23 Sep 2020 Tedd Kourkounakis, Amirhossein Hajavi, Ali Etemad

We also evaluate FluentNet on this dataset, showing the strong performance of our model versus a number of benchmark techniques.

automatic-speech-recognition Speech Recognition

Knowing What to Listen to: Early Attention for Deep Speech Representation Learning

no code implementations3 Sep 2020 Amirhossein Hajavi, Ali Etemad

Speech representations extracted by deep learning models are being used in a wide range of tasks such as speech recognition, speaker recognition, and speech emotion recognition.

Representation Learning Speaker Recognition +2

Unsupervised Multi-Modal Representation Learning for Affective Computing with Multi-Corpus Wearable Data

no code implementations24 Aug 2020 Kyle Ross, Paul Hungler, Ali Etemad

The results show the wide-spread applicability for stacked convolutional autoencoders to be used with machine learning for affective computing.

Emotion Recognition Representation Learning

RFNet: Riemannian Fusion Network for EEG-based Brain-Computer Interfaces

no code implementations19 Aug 2020 Guangyi Zhang, Ali Etemad

This paper presents the novel Riemannian Fusion Network (RFNet), a deep neural architecture for learning spatial and temporal information from Electroencephalogram (EEG) for a number of different EEG-based Brain Computer Interface (BCI) tasks and applications.

Decision Making EEG +4

Deep Multitask Learning for Pervasive BMI Estimation and Identity Recognition in Smart Beds

no code implementations18 Jun 2020 Vandad Davoodnia, Monet Slinowsky, Ali Etemad

Smart devices in the Internet of Things (IoT) paradigm provide a variety of unobtrusive and pervasive means for continuous monitoring of bio-metrics and health information.

Two-Level Attention-based Fusion Learning for RGB-D Face Recognition

1 code implementation29 Feb 2020 Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan, Ali Etemad

A novel attention aware method is proposed to fuse two image modalities, RGB and depth, for enhanced RGB-D facial recognition.

Face Recognition Transfer Learning

Self-supervised ECG Representation Learning for Emotion Recognition

2 code implementations4 Feb 2020 Pritam Sarkar, Ali Etemad

Six different signal transformations are applied to the ECG signals, and transformation recognition is performed as pretext tasks.

Emotion Recognition Multi-Task Learning +1

Capsule Attention for Multimodal EEG-EOG Representation Learning with Application to Driver Vigilance Estimation

no code implementations17 Dec 2019 Guangyi Zhang, Ali Etemad

To enable the system to focus on the most salient parts of the learned multimodal representations, we propose an architecture composed of a capsule attention mechanism following a deep Long Short-Term Memory (LSTM) network.

EEG Representation Learning

Self-supervised Learning for ECG-based Emotion Recognition

2 code implementations14 Oct 2019 Pritam Sarkar, Ali Etemad

Our proposed architecture consists of two main networks, a signal transformation recognition network and an emotion recognition network.

Emotion Recognition Self-Supervised Learning

In-bed Pressure-based Pose Estimation using Image Space Representation Learning

no code implementations21 Aug 2019 Vandad Davoodnia, Saeed Ghorbani, Ali Etemad

Recent advances in deep pose estimation models have proven to be effective in a wide range of applications such as health monitoring, sports, animations, and robotics.

Pose Estimation Representation Learning

Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network

no code implementations6 Aug 2019 Guangyi Zhang, Vandad Davoodnia, Alireza Sepas-Moghaddam, Yaoxue Zhang, Ali Etemad

Classifying limb movements using brain activity is an important task in Brain-computer Interfaces (BCI) that has been successfully used in multiple application domains, ranging from human-computer interaction to medical and biomedical applications.

Deep Attention EEG +2

Classification of Cognitive Load and Expertise for Adaptive Simulation using Deep Multitask Learning

no code implementations31 Jul 2019 Pritam Sarkar, Kyle Ross, Aaron J. Ruberto, Dirk Rodenburg, Paul Hungler, Ali Etemad

Simulations are a pedagogical means of enabling a risk-free way for healthcare practitioners to learn, maintain, or enhance their knowledge and skills.

General Classification

Auto-labelling of Markers in Optical Motion Capture by Permutation Learning

no code implementations31 Jul 2019 Saeed Ghorbani, Ali Etemad, Nikolaus F. Troje

Optical marker-based motion capture is a vital tool in applications such as motion and behavioural analysis, animation, and biomechanics.

Motion Capture

A Deep Neural Network for Short-Segment Speaker Recognition

no code implementations22 Jul 2019 Amirhossein Hajavi, Ali Etemad

Todays interactive devices such as smart-phone assistants and smart speakers often deal with short-duration speech segments.

Speaker Recognition

Long Short-Term Memory with Gate and State Level Fusion for Light Field-Based Face Recognition

no code implementations11 May 2019 Alireza Sepas-Moghaddam, Ali Etemad, Fernando Pereira, Paulo Lobato Correia

In this context, this paper proposes two novel LSTM cell architectures that are able to jointly learn from multiple sequences simultaneously acquired, targeting to create richer and more effective models for recognition tasks.

Face Recognition Time Series

Cannot find the paper you are looking for? You can Submit a new open access paper.