Search Results for author: Ali Etemad

Found 99 papers, 33 papers with code

Segment, Shuffle, and Stitch: A Simple Mechanism for Improving Time-Series Representations

1 code implementation30 May 2024 Shivam Grover, Amin Jalali, Ali Etemad

S3 works by creating non-overlapping segments from the original sequence and shuffling them in a learned manner that is the most optimal for the task at hand.

Representation Learning Time Series +1

Mitigating Object Hallucination via Data Augmented Contrastive Tuning

no code implementations28 May 2024 Pritam Sarkar, Sayna Ebrahimi, Ali Etemad, Ahmad Beirami, Sercan Ö. Arik, Tomas Pfister

For a given factual token, we create a hallucinated token through generative data augmentation by selectively altering the ground-truth information.

Data Augmentation Hallucination +1

Federated Unsupervised Domain Generalization using Global and Local Alignment of Gradients

no code implementations25 May 2024 Farhad Pourpanah, Mahdiyar Molahasani, Milad Soltany, Michael Greenspan, Ali Etemad

We first theoretically establish a connection between domain shift and alignment of gradients in unsupervised federated learning and show that aligning the gradients at both client and server levels can facilitate the generalization of the model to new (target) domains.

Domain Generalization Federated Learning

UPose3D: Uncertainty-Aware 3D Human Pose Estimation with Cross-View and Temporal Cues

no code implementations23 Apr 2024 Vandad Davoodnia, Saeed Ghorbani, Marc-André Carbonneau, Alexandre Messier, Ali Etemad

At the core of our method, a pose compiler module refines predictions from a 2D keypoints estimator that operates on a single image by leveraging temporal and cross-view information.

3D Human Pose Estimation Synthetic Data Generation

SkelFormer: Markerless 3D Pose and Shape Estimation using Skeletal Transformers

no code implementations19 Apr 2024 Vandad Davoodnia, Saeed Ghorbani, Alexandre Messier, Ali Etemad

Next, we design a regression-based inverse-kinematic skeletal transformer that maps the joint positions to pose and shape representations from heavily noisy observations.

Keypoint Detection Markerless Motion Capture

Learning under Label Noise through Few-Shot Human-in-the-Loop Refinement

no code implementations25 Jan 2024 Aaqib Saeed, Dimitris Spathis, JungWoo Oh, Edward Choi, Ali Etemad

We show that FHLR achieves significantly better performance when learning from noisy labels and achieves state-of-the-art by a large margin, with up to 19% accuracy improvement under symmetric and asymmetric noise.

Contrastive Learning of View-Invariant Representations for Facial Expressions Recognition

no code implementations12 Nov 2023 Shuvendu Roy, Ali Etemad

ViewFX learns view-invariant features of expression using a proposed self-supervised contrastive loss which brings together different views of the same subject with a particular expression in the embedding space.

Contrastive Learning Facial Expression Recognition +1

Remote Heart Rate Monitoring in Smart Environments from Videos with Self-supervised Pre-training

no code implementations23 Oct 2023 Divij Gupta, Ali Etemad

Recent advances in deep learning have made it increasingly feasible to estimate heart rate remotely in smart environments by analyzing videos.

Contrastive Learning Heart rate estimation +2

Speech Emotion Recognition with Distilled Prosodic and Linguistic Affect Representations

no code implementations9 Sep 2023 Debaditya Shome, Ali Etemad

We propose EmoDistill, a novel speech emotion recognition (SER) framework that leverages cross-modal knowledge distillation during training to learn strong linguistic and prosodic representations of emotion from speech.

Knowledge Distillation Speech Emotion Recognition

Diffusion Models with Deterministic Normalizing Flow Priors

1 code implementation3 Sep 2023 Mohsen Zand, Ali Etemad, Michael Greenspan

We use normalizing flows to parameterize the noisy data at any arbitrary step of the diffusion process and utilize it as the prior in the reverse diffusion process.

Denoising Image Generation

Multiscale Residual Learning of Graph Convolutional Sequence Chunks for Human Motion Prediction

1 code implementation31 Aug 2023 Mohsen Zand, Ali Etemad, Michael Greenspan

Our experiments on two challenging benchmark datasets, CMU Mocap and Human3. 6M, demonstrate that our proposed method is able to effectively model the sequence information for motion prediction and outperform other techniques to set a new state-of-the-art.

Human motion prediction Human Pose Forecasting +1

Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation

1 code implementation25 Aug 2023 Debaditya Shome, Pritam Sarkar, Ali Etemad

In this work, we introduce Region-Disentangled Diffusion Model (RDDM), a novel diffusion model designed to capture the complex temporal dynamics of ECG.

Blood pressure estimation Denoising +2

EEG-based Cognitive Load Classification using Feature Masked Autoencoding and Emotion Transfer Learning

no code implementations1 Aug 2023 Dustin Pulver, Prithila Angkan, Paul Hungler, Ali Etemad

We pre-train our model using self-supervised masked autoencoding on emotion-related EEG datasets and use transfer learning with both frozen weights and fine-tuning to perform downstream cognitive load classification.

Classification Decision Making +2

Context-aware Pedestrian Trajectory Prediction with Multimodal Transformer

no code implementations7 Jul 2023 Haleh Damirchi, Michael Greenspan, Ali Etemad

Quantitative results demonstrate the superiority of our proposed model over the current state-of-the-art, which consistently achieves the lowest error for 3 time horizons of 0. 5, 1. 0 and 1. 5 seconds.

Decoder Pedestrian Trajectory Prediction +1

Active Learning with Contrastive Pre-training for Facial Expression Recognition

1 code implementation6 Jul 2023 Shuvendu Roy, Ali Etemad

Even though some prior works have focused on reducing the need for large amounts of labelled data using different unsupervised methods, another promising approach called active learning is barely explored in the context of FER.

Active Learning Facial Expression Recognition +1

Continual Learning for Out-of-Distribution Pedestrian Detection

1 code implementation26 Jun 2023 Mahdiyar Molahasani, Ali Etemad, Michael Greenspan

A continual learning solution is proposed to address the out-of-distribution generalization problem for pedestrian detection.

Continual Learning object-detection +3

Can Continual Learning Improve Long-Tailed Recognition? Toward a Unified Framework

no code implementations23 Jun 2023 Mahdiyar Molahasani, Michael Greenspan, Ali Etemad

Next, we assert that by treating the learning of the Head and Tail as two separate and sequential steps, Continual Learning (CL) methods can effectively update the weights of the learner to learn the Tail without forgetting the Head.

Continual Learning

Unmasking Deepfakes: Masked Autoencoding Spatiotemporal Transformers for Enhanced Video Forgery Detection

no code implementations12 Jun 2023 Sayantan Das, Mojtaba Kolahdouzi, Levent Özparlak, Will Hickie, Ali Etemad

We present a novel approach for the detection of deepfake videos using a pair of vision transformers pre-trained by a self-supervised masked autoencoding setup.

Face Swapping Optical Flow Estimation

Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data

1 code implementation2 Jun 2023 Shuvendu Roy, Ali Etemad

We propose UnMixMatch, a semi-supervised learning framework which can learn effective representations from unconstrained unlabelled data in order to scale up performance.

Network Pruning Semi-Supervised Image Classification

Consistency-guided Prompt Learning for Vision-Language Models

2 code implementations1 Jun 2023 Shuvendu Roy, Ali Etemad

Our approach improves the generalization of large foundation models when fine-tuned on downstream tasks in a few-shot setting.

Domain Generalization Few-Shot Learning +1

An Ensemble Semi-Supervised Adaptive Resonance Theory Model with Explanation Capability for Pattern Classification

no code implementations19 May 2023 Farhad Pourpanah, Chee Peng Lim, Ali Etemad, Q. M. Jonathan Wu

Firstly, SSL-ART adopts an unsupervised fuzzy ART network to create a number of prototype nodes using unlabeled samples.

In-Distribution and Out-of-Distribution Self-supervised ECG Representation Learning for Arrhythmia Detection

no code implementations13 Apr 2023 Sahar Soltanieh, Javad Hashemi, Ali Etemad

To further assess the performance of these methods on both In-Distribution (ID) and Out-of-Distribution (OOD) ECG data, we conduct cross-dataset training and testing experiments.

Arrhythmia Detection Representation Learning +1

Multimodal Brain-Computer Interface for In-Vehicle Driver Cognitive Load Measurement: Dataset and Baselines

no code implementations9 Apr 2023 Prithila Angkan, Behnam Behinaein, Zunayed Mahmud, Anubhav Bhatti, Dirk Rodenburg, Paul Hungler, Ali Etemad

Through this paper, we introduce a novel driver cognitive load assessment dataset, CL-Drive, which contains Electroencephalogram (EEG) signals along with other physiological signals such as Electrocardiography (ECG) and Electrodermal Activity (EDA) as well as eye tracking data.

Brain Computer Interface EEG +1

A Study on Bias and Fairness In Deep Speaker Recognition

no code implementations14 Mar 2023 Amirhossein Hajavi, Ali Etemad

With the ubiquity of smart devices that use speaker recognition (SR) systems as a means of authenticating individuals and personalizing their services, fairness of SR systems has becomes an important point of focus.

Fairness Speaker Recognition

Human Pose Estimation from Ambiguous Pressure Recordings with Spatio-temporal Masked Transformers

no code implementations10 Mar 2023 Vandad Davoodnia, Ali Etemad

Moreover, we observe that increasing the number of temporal crops in the early stages of the network positively impacts the performance while pre-training the network in a self-supervised setting using a masked auto-encoder approach also further improves the results.

Decoder Pose Estimation

Partial Label Learning for Emotion Recognition from EEG

1 code implementation25 Feb 2023 Guangyi Zhang, Ali Etemad

However, PLL methods have not yet been adopted for EEG representation learning or implemented for emotion recognition tasks.

EEG Emotion Recognition +2

Audio Representation Learning by Distilling Video as Privileged Information

no code implementations6 Feb 2023 Amirhossein Hajavi, Ali Etemad

In this work, we propose a novel approach for deep audio representation learning using audio-visual data when the video modality is absent at inference.

Knowledge Distillation Representation Learning +2

Impact of Labelled Set Selection and Supervision Policies on Semi-supervised Learning

no code implementations27 Nov 2022 Shuvendu Roy, Ali Etemad

All these labelled samples are then used along with the unlabelled data throughout the training process.

Representation Learning

FaceTopoNet: Facial Expression Recognition using Face Topology Learning

no code implementations13 Sep 2022 Mojtaba Kolahdouzi, Alireza Sepas-Moghaddam, Ali Etemad

We perform extensive experiments on four large-scale in-the-wild facial expression datasets - namely AffectNet, FER2013, ExpW, and RAF-DB - and one lab-controlled dataset (CK+) to evaluate our approach.

Facial Expression Recognition Facial Expression Recognition (FER)

Temporal Contrastive Learning with Curriculum

no code implementations2 Sep 2022 Shuvendu Roy, Ali Etemad

We present ConCur, a contrastive video representation learning method that uses curriculum learning to impose a dynamic sampling strategy in contrastive training.

Action Recognition Contrastive Learning +4

Self-Supervised Human Activity Recognition with Localized Time-Frequency Contrastive Representation Learning

no code implementations26 Aug 2022 Setareh Rahimi Taghanaki, Michael Rainbow, Ali Etemad

We aim to develop a model that learns strong representations from accelerometer signals, in order to perform robust human activity classification, while reducing the model's reliance on class labels.

Classification Contrastive Learning +4

Analysis of Semi-Supervised Methods for Facial Expression Recognition

2 code implementations31 Jul 2022 Shuvendu Roy, Ali Etemad

To reduce the reliance of deep neural solutions on labeled data, state-of-the-art semi-supervised methods have been proposed in the literature.

Facial Expression Recognition Facial Expression Recognition (FER) +1

Multimodal Estimation of End Point Force During Quasi-dynamic and Dynamic Muscle Contractions Using Deep Learning

no code implementations20 Jul 2022 Gelareh Hajian, Evelyn Morin, Ali Etemad

We propose a novel method to accurately model the generated force under isotonic, isokinetic (quasi-dynamic), and fully dynamic conditions.

ObjectBox: From Centers to Boxes for Anchor-Free Object Detection

1 code implementation14 Jul 2022 Mohsen Zand, Ali Etemad, Michael Greenspan

We present ObjectBox, a novel single-stage anchor-free and highly generalizable object detection approach.

Object object-detection +1

Multistream Gaze Estimation with Anatomical Eye Region Isolation by Synthetic to Real Transfer Learning

1 code implementation18 Jun 2022 Zunayed Mahmud, Paul Hungler, Ali Etemad

The eye region isolation is performed with a U-Net style network which we train using a synthetic dataset that contains eye region masks for the visible eyeball and the iris region.

Anatomy Gaze Estimation +1

Estimating Pose from Pressure Data for Smart Beds with Deep Image-based Pose Estimators

no code implementations13 Jun 2022 Vandad Davoodnia, Saeed Ghorbani, Ali Etemad

In-bed pose estimation has shown value in fields such as hospital patient monitoring, sleep studies, and smart homes.

Domain Adaptation Pose Estimation

AttX: Attentive Cross-Connections for Fusion of Wearable Signals in Emotion Recognition

no code implementations9 Jun 2022 Anubhav Bhatti, Behnam Behinaein, Paul Hungler, Ali Etemad

We perform extensive experiments on three public multimodal wearable datasets, WESAD, SWELL-KW, and CASE, and demonstrate that our method can effectively regulate and share information between different modalities to learn better representations.

Emotion Recognition Representation Learning

Learning Sequential Contexts using Transformer for 3D Hand Pose Estimation

no code implementations1 Jun 2022 Leyla Khaleghi, Joshua Marshall, Ali Etemad

3D hand pose estimation (HPE) is the process of locating the joints of the hand in 3D from any visual input.

3D Hand Pose Estimation

Analysis of Augmentations for Contrastive ECG Representation Learning

no code implementations30 May 2022 Sahar Soltanieh, Ali Etemad, Javad Hashemi

For instance, when adding Gaussian noise, a sigma in the range of 0. 1 to 0. 2 achieves better results, while poor training occurs when the added noise is too small or too large (outside of the specified range).

Arrhythmia Detection Contrastive Learning +2

AVCAffe: A Large Scale Audio-Visual Dataset of Cognitive Load and Affect for Remote Work

1 code implementation13 May 2022 Pritam Sarkar, Aaron Posen, Ali Etemad

We introduce AVCAffe, the first Audio-Visual dataset consisting of Cognitive load and Affect attributes.


Multiscale Crowd Counting and Localization By Multitask Point Supervision

1 code implementation21 Feb 2022 Mohsen Zand, Haleh Damirchi, Andrew Farley, Mahdiyar Molahasani, Michael Greenspan, Ali Etemad

As the detection and localization tasks are well-correlated and can be jointly tackled, our model benefits from a multitask solution by learning multiscale representations of encoded crowd images, and subsequently fusing them.

Crowd Counting

PARSE: Pairwise Alignment of Representations in Semi-Supervised EEG Learning for Emotion Recognition

1 code implementation11 Feb 2022 Guangyi Zhang, Vandad Davoodnia, Ali Etemad

To reduce the potential distribution mismatch between the large amounts of unlabeled data and the limited amount of labeled data, PARSE uses pairwise representation alignment.

Data Augmentation EEG +2

Gaze Estimation with Eye Region Segmentation and Self-Supervised Multistream Learning

no code implementations15 Dec 2021 Zunayed Mahmud, Paul Hungler, Ali Etemad

We first create a synthetic dataset containing eye region masks detailing the visible eyeball and iris using a simulator.

Contrastive Learning Gaze Estimation

Towards Personalization of User Preferences in Partially Observable Smart Home Environments

no code implementations2 Dec 2021 Shashi Suman, Francois Rivest, Ali Etemad

In this paper, we propose a Bayesian Reinforcement learning framework that can approximate the current occupant state in a partially observable smart home environment using its thermal preference, and then identify the occupant as a new user or someone is already known to the system.

Hierarchical Reinforcement Learning reinforcement-learning +1

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.


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 +1

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.

Novel Object Detection object-detection +1

Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics

1 code implementation9 Apr 2021 Mohsen Zand, Ali Etemad, Michael Greenspan

We specifically propose to use conditional priors to factorize the latent space for the time dependent modeling.

motion prediction Structured Prediction +3

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 Generative Adversarial Network +1

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

1 code implementation6 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 fewer, more disperse keypoints.

 Ranked #1 on 6D Pose Estimation using RGBD on YCB-Video (ADDS AUC metric)

6D Pose Estimation using RGBD

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 +2

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

2 code implementations3 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

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

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

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.

Generative Adversarial Network

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

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 Automatic Speech Recognition (ASR) +1

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

1 code implementation23 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.

Fine-grained Early Frequency Attention for Deep Speaker Representation Learning

no code implementations3 Sep 2020 Amirhossein Hajavi, Ali Etemad

We evaluate the proposed model on three tasks of speaker recognition, speech emotion recognition, and spoken digit recognition.

Representation Learning Speaker Recognition +3

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.

BIG-bench Machine Learning Emotion Recognition +1

Spatio-Temporal EEG Representation Learning on Riemannian Manifold and Euclidean Space

1 code implementation19 Aug 2020 Guangyi Zhang, Ali Etemad

Moreover, our proposed method learns the temporal information via differential entropy and logarithm power spectrum density features extracted from EEG signals in a Euclidean space using a deep long short-term memory network with a soft attention mechanism.

Binary Classification Decision Making +6

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.

BIG-bench Machine Learning

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 +1

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.

Brain Computer Interface EEG +1

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 +3

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.

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.

Benchmarking Face Recognition +1

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