Hieu H. Pham

Orcid: 0000-0003-4851-2518

Affiliations:
  • VinUniversity, VinUni-Illinois Smart Health Center, Vingroup Big Data Institut, College of Engineering and Computer Science, Hanoi, Vietnam
  • University of Toulouse, Toulouse Computer Science Research Institute, IRIT, France (PhD 2019)


According to our database1, Hieu H. Pham authored at least 63 papers between 2018 and 2024.

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Bibliography

2024
MPCNN: A Novel Matrix Profile Approach for CNN-based Single Lead Sleep Apnea in Classification Problem.
IEEE J. Biomed. Health Informatics, August, 2024

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource-Constrained Devices Using Divide and Collaborative Training.
IEEE Trans. Netw. Serv. Manag., February, 2024

Backdoor attacks and defenses in federated learning: Survey, challenges and future research directions.
Eng. Appl. Artif. Intell., January, 2024

GAMMA: A universal model for calibrating sensory data of multiple low-cost air monitoring devices.
Eng. Appl. Artif. Intell., 2024

SarcNet: A Novel AI-based Framework to Automatically Analyze and Score Sarcomere Organizations in Fluorescently Tagged hiPSC-CMs.
CoRR, 2024

ConPro: Learning Severity Representation for Medical Images using Contrastive Learning and Preference Optimization.
CoRR, 2024

MSTAR: Multi-Scale Backbone Architecture Search for Timeseries Classification.
CoRR, 2024

Training-Free Condition Video Diffusion Models for Single Frame Spatial-Semantic Echocardiogram Synthesis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023
LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification.
Biomed. Signal Process. Control., August, 2023

IncepSE: Leveraging InceptionTime's performance with Squeeze and Excitation mechanism in ECG analysis.
CoRR, 2023

Learning to Estimate Critical Gait Parameters from Single-View RGB Videos with Transformer-Based Attention Network.
CoRR, 2023

MPCNN: A Novel Matrix Profile Approach for CNN-based Sleep Apnea Classification.
CoRR, 2023

TransReg: Cross-transformer as auto-registration module for multi-view mammogram mass detection.
CoRR, 2023

Echocardiography video synthesis from end diastolic semantic map via diffusion model.
CoRR, 2023

Echocardiography Segmentation Using Neural ODE-based Diffeomorphic Registration Field.
CoRR, 2023

Learning Robust and Consistent Time Series Representations: A Dilated Inception-Based Approach.
CoRR, 2023

FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection.
CoRR, 2023

Multimodal contrastive learning for diagnosing cardiovascular diseases from electrocardiography (ECG) signals and patient metadata.
CoRR, 2023

Evaluating the impact of an explainable machine learning system on the interobserver agreement in chest radiograph interpretation.
CoRR, 2023

Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation.
CoRR, 2023

High Accurate and Explainable Multi-Pill Detection Framework with Graph Neural Network-Assisted Multimodal Data Fusion.
CoRR, 2023

Ensemble Learning of Myocardial Displacements for Myocardial Infarction Detection in Echocardiography.
CoRR, 2023

Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning.
CoRR, 2023

Enhancing Few-Shot Image Classification With Cosine Transformer.
IEEE Access, 2023

Learning From Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis.
IEEE Access, 2023

A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

A Novel Approach for Extracting Key Information from Vietnamese Prescription Images.
Proceedings of the 12th International Symposium on Information and Communication Technology, 2023

IncepSE: Leveraging InceptionTime's performance with Squeeze and Excitaion mechanism in ECG analysis.
Proceedings of the 12th International Symposium on Information and Communication Technology, 2023

FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection.
Proceedings of the International Joint Conference on Neural Networks, 2023

CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

SEM: A Simple Yet Efficient Model-agnostic Local Training Mechanism to Tackle Data Sparsity and Scarcity in Federated Learning.
Proceedings of the Eleventh International Symposium on Computing and Networking, CANDAR 2023, Matsue, Japan, November 28, 2023

2022
Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings.
Frontiers Digit. Health, 2022

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Co-Training.
CoRR, 2022

Enhancing Few-shot Image Classification with Cosine Transformer.
CoRR, 2022

Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese.
CoRR, 2022

Enhancing Deep Learning-based 3-lead ECG Classification with Heartbeat Counting and Demographic Data Integration.
CoRR, 2022

Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks.
CoRR, 2022

Video-based Human Action Recognition using Deep Learning: A Review.
CoRR, 2022

A novel deep learning-based approach for sleep apnea detection using single-lead ECG signals.
CoRR, 2022

FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning.
CoRR, 2022

Image-based Contextual Pill Recognition with Medical Knowledge Graph Assistance.
CoRR, 2022

Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling.
CoRR, 2022

VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography.
CoRR, 2022

VinDr-PCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children.
CoRR, 2022

Transparency strategy-based data augmentation for BI-RADS classification of mammograms.
CoRR, 2022

An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph.
IEEE Access, 2022

A Novel Approach for Pill-Prescription Matching with GNN Assistance and Contrastive Learning.
Proceedings of the PRICAI 2022: Trends in Artificial Intelligence, 2022

FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning.
Proceedings of the 51st International Conference on Parallel Processing, 2022

A novel multi-view deep learning approach for BI-RADS and density assessment of mammograms.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Image-Based Contextual Pill Recognition with Medical Knowledge Graph Assistance.
Proceedings of the Recent Challenges in Intelligent Information and Database Systems, 2022

Multi-stream Fusion for Class Incremental Learning in Pill Image Classification.
Proceedings of the Computer Vision - ACCV 2022, 2022

2021
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels.
Neurocomputing, 2021

DICOM Imaging Router: An Open Deep Learning Framework for Classification of Body Parts from DICOM X-ray Scans.
CoRR, 2021

VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays.
CoRR, 2021

A clinical validation of VinDr-CXR, an AI system for detecting abnormal chest radiographs.
CoRR, 2021

VinDr-SpineXR: A Deep Learning Framework for Spinal Lesions Detection and Classification from Radiographs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2020
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera.
Sensors, 2020

2019
Spatio-Temporal Image Representation of 3D Skeletal Movements for View-Invariant Action Recognition with Deep Convolutional Neural Networks.
Sensors, 2019

Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels.
CoRR, 2019

A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data.
Proceedings of the Image Analysis and Recognition - 16th International Conference, 2019

2018
Exploiting deep residual networks for human action recognition from skeletal data.
Comput. Vis. Image Underst., 2018


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