| Machine learning-based mortality prediction of patients undergoing cardiac resynchronization therapy: the SEMMELWEIS-CRT score M Tokodi, WR Schwertner, A Kovács, Z Tősér, L Staub, A Sárkány, ... European heart journal 41 (18), 1747-1756, 2020 | 119 | 2020 |
| LabelMovie: Semi-supervised machine annotation tool with quality assurance and crowd-sourcing options for videos Z Palotai, M Láng, A Sárkány, Z Tősér, D Sonntag, T Toyama, A Lőrincz 2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI …, 2014 | 22 | 2014 |
| Sex-specific patterns of mortality predictors among patients undergoing cardiac resynchronization therapy: a machine learning approach M Tokodi, A Behon, ED Merkel, A Kovács, Z Tősér, A Sárkány, M Csákvári, ... Frontiers in Cardiovascular Medicine 8, 611055, 2021 | 19 | 2021 |
| On-body multi-input indoor localization for dynamic emergency scenarios: fusion of magnetic tracking and optical character recognition with mixed-reality display J Orlosky, T Toyama, D Sonntag, A Sarkany, A Lorincz 2014 IEEE International Conference on Pervasive Computing and Communication …, 2014 | 14 | 2014 |
| Maintain and improve mental health by smart virtual reality serious games A Sárkány, Z Tősér, AL Verő, A Lőrincz, T Toyama, EN Toosi, D Sonntag Pervasive Computing Paradigms for Mental Health: 5th International …, 2016 | 12 | 2016 |
| Towards reasoning based representations: Deep consistence seeking machine A Lőrincz, M Csákvári, Á Fóthi, ZÁ Milacski, A Sárkány, Z Tősér Cognitive Systems Research 47, 92-108, 2018 | 9 | 2018 |
| Composite AI for behavior analysis in social interactions BC Dos Santos Melicio, L Xiang, E Dillon, L Soorya, M Chetouani, ... Companion Publication of the 25th International Conference on Multimodal …, 2023 | 6 | 2023 |
| Semi-supervised learning of cartesian factors: a top-down model of the entorhinal hippocampal complex A Lőrincz, A Sárkány Frontiers in Psychology 8, 215, 2017 | 6 | 2017 |
| Estimating cartesian compression via deep learning A Lőrincz, A Sárkány, ZÁ Milacski, Z Tősér Artificial General Intelligence: 9th International Conference, AGI 2016, New …, 2016 | 5 | 2016 |
| Recommending Missing Symbols of Augmentative and Alternative Communication by Means of Explicit Semantic Analysis. G Vörös, P Rabi, B Pintér, A Sárkány, D Sonntag, A Lörincz AAAI Fall Symposia, 2014 | 5 | 2014 |
| Cognitive deep machine can train itself A Lőrincz, M Csákvári, Á Fóthi, ZÁ Milacski, A Sárkány, Z Tősér arXiv preprint arXiv:1612.00745, 2016 | 3 | 2016 |
| Exploring sex-specific patterns of mortality predictors among patients undergoing cardiac resynchronization therapy: a machine learning approach M Tokodi, A Behon, ED Merkel, A Kovacs, Z Toser, A Sarkany, M Csakvari, ... European Heart Journal 41 (Supplement_2), ehaa946. 0996, 2020 | 2 | 2020 |
| Artificial intelligence-enabled reconstruction of the right ventricular pressure curve using the peak pressure value: a proof-of-concept study Á Szijártó, A Nicoara, M Podgoreanu, M Tokodi, A Fábián, B Merkely, ... European Heart Journal-Imaging Methods and Practice 2 (4), qyae099, 2024 | | 2024 |
| Naturalistic, Non-Invasive Method for Capturing Biometric Data during Autism Diagnostic Evaluations K Kamal, A Sarkany, CW Brune, EF Dillon, LV Soorya, Z Tősér INSAR 2023, 2023 | | 2023 |
| Combining Common Sense Rules and Machine Learning to Understand Object Manipulation A Sárkány, M Csákvári, M Olasz Acta Cybernetica 24 (1), 157-172, 2019 | | 2019 |
| Towards the understanding of object manipulations by means of combining common sense rules and deep networks M Csákvári, A Sárkány THE 11TH CONFERENCE OF PHD STUDENTS IN COMPUTER SCIENCE, 118, 2018 | | 2018 |
| Semi-Supervised Learning of Cartesian Factors A Lorincz, A Sárkány | | 2017 |
