Hieu H. Pham
Orcid: 0000-0003-4851-2518Affiliations:
- 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 43 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
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
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
FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection.
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
CoRR, 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
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
Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese.
CoRR, 2022
FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning.
CoRR, 2022
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
Proceedings of the Recent Challenges in Intelligent Information and Database Systems, 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
Comput. Vis. Image Underst., 2018