Cover Image

Accurate and Private Diagnosis of Rare Genetic Syndromes from Facial Images with Federated Deep Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ünal, Ali Burak, Baykara, Cem Ata, Krawitz, Peter, Akgün, Mete
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Cryptography and Security Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enabling Privacy-preserving Model Evaluation in Federated Learning via Fully Homomorphic Encryption
by: Baykara, Cem Ata, et al.
Published: (2024)

Private, Efficient and Scalable Kernel Learning for Medical Image Analysis
by: Hannemann, Anika, et al.
Published: (2024)

CECILIA: Comprehensive Secure Machine Learning Framework
by: Ünal, Ali Burak, et al.
Published: (2022)

Accelerating Privacy-Preserving Medical Record Linkage: A Three-Party MPC Approach
by: Mağara, Şeyma Selcan, et al.
Published: (2024)

PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies
by: Swaminathan, Arjhun, et al.
Published: (2024)

Privacy Preserving Data Imputation via Multi-party Computation for Medical Applications
by: Jentsch, Julia, et al.
Published: (2024)

Privacy-Preserving Federated Unsupervised Domain Adaptation for Regression on Small-Scale and High-Dimensional Biological Data
by: Baykara, Cem Ata, et al.
Published: (2024)

A Privacy-Preserving Federated Learning Approach for Kernel methods
by: Hannemann, Anika, et al.
Published: (2023)

Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets
by: Baykara, Cem Ata, et al.
Published: (2025)

Scaling Unsupervised Multi-Source Federated Domain Adaptation through Group-Wise Discrepancy Minimization
by: Reichart, Larissa, et al.
Published: (2025)

QA-HFL: Quality-Aware Hierarchical Federated Learning for Resource-Constrained Mobile Devices with Heterogeneous Image Quality
by: Hussain, Sajid, et al.
Published: (2025)

Adversarially Guided Stateful Defense Against Backdoor Attacks in Federated Deep Learning
by: Ali, Hassan, et al.
Published: (2024)

Federated Learning for Large Models in Medical Imaging: A Comprehensive Review
by: Sun, Mengyu, et al.
Published: (2025)

FRIDAY: Mitigating Unintentional Facial Identity in Deepfake Detectors Guided by Facial Recognizers
by: Kim, Younhun, et al.
Published: (2024)

Decomposing Private Image Generation via Coarse-to-Fine Wavelet Modeling
by: Bayrooti, Jasmine, et al.
Published: (2026)

Differential Anomaly Detection for Facial Images
by: Ibsen, Mathias, et al.
Published: (2021)

Blind Deep-Learning-Based Image Watermarking Robust Against Geometric Transformations
by: Mareen, Hannes, et al.
Published: (2024)

DLOVE: A new Security Evaluation Tool for Deep Learning Based Watermarking Techniques
by: Padhi, Sudev Kumar, et al.
Published: (2024)

From Easy to Hard++: Promoting Differentially Private Image Synthesis Through Spatial-Frequency Curriculum
by: Gong, Chen, et al.
Published: (2026)

Facial Recognition Leveraging Generative Adversarial Networks
by: Li, Zhongwen, et al.
Published: (2025)

Solutions to Deepfakes: Can Camera Hardware, Cryptography, and Deep Learning Verify Real Images?
by: Vilesov, Alexander, et al.
Published: (2024)

CamPro: Camera-based Anti-Facial Recognition
by: Zhu, Wenjun, et al.
Published: (2023)

Private Gradient Estimation is Useful for Generative Modeling
by: Liu, Bochao, et al.
Published: (2023)

pfl-research: simulation framework for accelerating research in Private Federated Learning
by: Granqvist, Filip, et al.
Published: (2024)

Arc2Morph: Identity-Preserving Facial Morphing with Arc2Face
by: Di Domenico, Nicolò, et al.
Published: (2026)

DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection
by: Liu, Jiang, et al.
Published: (2023)

Crafter: Facial Feature Crafting against Inversion-based Identity Theft on Deep Models
by: Wang, Shiming, et al.
Published: (2024)

Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning
by: Jia, Yuqi, et al.
Published: (2024)

Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning
by: Zhao, Joshua C., et al.
Published: (2024)

Nebula: Efficient, Private and Accurate Histogram Estimation
by: Shamsabadi, Ali Shahin, et al.
Published: (2024)

IPBA: Imperceptible Perturbation Backdoor Attack in Federated Self-Supervised Learning
by: Wang, Jiayao, et al.
Published: (2025)

Intrusion Detection: A Deep Learning Approach
by: Shivhare, Ishaan, et al.
Published: (2023)

PuFace: Defending against Facial Cloaking Attacks for Facial Recognition Models
by: Wen, Jing
Published: (2024)

Frequency Bias Matters: Diving into Robust and Generalized Deep Image Forgery Detection
by: Liu, Chi, et al.
Published: (2025)

Deep Multi-Task Learning for Malware Image Classification
by: Bensaoud, Ahmed, et al.
Published: (2024)

FaceSwapGuard: Safeguarding Facial Privacy from DeepFake Threats through Identity Obfuscation
by: Wang, Li, et al.
Published: (2025)

Privacy-Preserving Federated Learning with Verifiable Fairness Guarantees
by: Ali, Mohammed Himayath, et al.
Published: (2026)

FedBlock: A Blockchain Approach to Federated Learning against Backdoor Attacks
by: Nguyen, Duong H., et al.
Published: (2024)

Robust and Transferable Backdoor Attacks Against Deep Image Compression With Selective Frequency Prior
by: Yu, Yi, et al.
Published: (2024)

DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR Strategy
by: Fan, Wenshu, et al.
Published: (2025)