Tamás Karácsony

According to our database, Tamás Karácsony authored at least 10 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Video-based epileptic seizure classification: A novel multi-stage approach integrating vision and motion transformer deep learning models.

Rojan Aslani, Tamás Karácsony, Nicholas Fearns, Catarina Caldeiras, Christian Vollmar, Ricardo Rego, Jan Rémi, Soheyl Noachtar, João Paulo Silva Cunha

Biomed. Signal Process. Control., 2026

2025

BlanketGen2-Fit3D: Synthetic Blanket Augmentation Towards Improving Real-World In-Bed Blanket Occluded Human Pose Estimation.

Tamás Karácsony, João Carmona, João Paulo Silva Cunha

CoRR, January, 2025

Exploring image and skeleton-based action recognition approaches for clinical in-bed classification of simulated epileptic seizure movements.

Tamás Karácsony, Nicholas Fearns, Denise Birk, Selina Denise Trapp, Katharina Ernst, Christian Vollmar, Jan Rémi, László Attila Jeni, Fernando De la Torre, João Paulo Silva Cunha

Expert Syst. Appl., 2025

2024

Deep learning methods for single camera based clinical in-bed movement action recognition.

Tamás Karácsony, László Attila Jeni, Fernando De la Torre, João Paulo Silva Cunha

Image Vis. Comput., 2024

NeuroKinect4K: A Novel 4K RGB-D-IR Video System with 3D Scene Reconstruction for Enhanced Epileptic Seizure Semiology Monitoring.

Tamás Karácsony, Nicholas Fearns, Christian Vollmar, Denise Birk, Jan Rémi, Soheyl Noachtar, João Paulo Silva Cunha

Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

2022

BlanketGen - A synthetic blanket occlusion augmentation pipeline for MoCap datasets.

João Carmona, Tamás Karácsony, João Paulo Silva Cunha

CoRR, 2022

BlanketSet - A clinical real word action recognition and qualitative semi-synchronised MoCap dataset.

João Carmona, Tamás Karácsony, João Paulo Silva Cunha

CoRR, 2022

2021

DeepEpil: Towards an Epileptologist-Friendly AI Enabled Seizure Classification Cloud System based on Deep Learning Analysis of 3D videos.

Tamás Karácsony, Anna Mira Loesch-Biffar, Christian Vollmar, Soheyl Noachtar, João Paulo Silva Cunha

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2021

2020

A Deep Learning Architecture for Epileptic Seizure Classification Based on Object and Action Recognition.

Tamás Karácsony, Anna Mira Loesch-Biffar, Christian Vollmar, Soheyl Noachtar, João Paulo Silva Cunha

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Brain Computer Interface for Neuro-rehabilitation With Deep Learning Classification and Virtual Reality Feedback.

Tamás Karácsony, John Paulin Hansen, Helle Klingenberg Iversen, Sadasivan Puthusserypady

Proceedings of the 10th Augmented Human International Conference 2019, 2019