| Fine-tuning deep CNN models on specific MS COCO categories D Sonntag, M Barz, J Zacharias, S Stauden, V Rahmani, A Fóthi, ... arXiv preprint arXiv:1709.01476, 2017 | 15 | 2017 |
| 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 |
| A self-supervised method for body part segmentation and keypoint detection of rat images L Kopácsi, A Fóthi, A Lőrincz arXiv preprint arXiv:2405.04650, 2024 | 4 | 2024 |
| RATS: Robust Automated Tracking and Segmentation of Similar Instances L Kopácsi, Á Dobolyi, Á Fóthi, D Keller, V Varga, A Lőrincz International Conference on Artificial Neural Networks, 507-518, 2021 | 4 | 2021 |
| Multi object tracking for similar instances: a hybrid architecture Á Fóthi, KB Faragó, L Kopácsi, ZÁ Milacski, V Varga, A Lőrincz Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020 | 4 | 2020 |
| Cognitive deep machine can train itself A Lőrincz, M Csákvári, Á Fóthi, ZA Milacski, A Sárkány, Z Tősér arXiv preprint arXiv:1612.00745, 2016 | 3 | 2016 |
| Cluster2former: Semisupervised clustering transformers for video instance segmentation Á Fóthi, A Szlatincsán, E Somfai Sensors 24 (3), 997, 2024 | 2 | 2024 |
| Declarative description: The meeting point of artificial intelligence deep neural networks and human intelligence Z Milacski, K Faragó, A Fóthi, V Varga, A Lorincz XAI 2018, Proceedings of the 2nd Workshop on Explainable Artificial …, 2018 | 2 | 2018 |
| Deep NRSFM for multi-view multi-body pose estimation Á Fóthi, J Skaf, F Lu, K Fenech Pattern Recognition Letters 185, 218-224, 2024 | 1 | 2024 |
| Adversarial perturbation stability of the layered group basis pursuit D Szeghy, ZA Milacski, A Fóthi, A Lorincz def 1, 2, 2021 | 1 | 2021 |
| Skeletonization Combined with Deep Neural Networks for Superpixel Temporal Propagation Á Fodor, Á Fóthi, L Kopácsi, E Somfai, A Lőrincz 2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019 | 1 | 2019 |
| Deep Gestalt Reasoning Model: Interpreting Electrophysiological Signals Related to Cognition A Lorincz, Á Fóthi, BO Rahman, V Varga Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 1 | 2017 |
| Skel3D: Skeleton Guided Novel View Synthesis A Fóthi, B Fazekas, NM Gyöngyössy, K Fenech arXiv preprint arXiv:2412.03407, 2024 | | 2024 |
| A SELF-SUPERVISED METHOD FOR BODY PART SEGMENTATION AND KEYPOINT DETECTION OF RAT IMAGES. Á Fóthi, L Kopácsi, A Lőrincz Annales Universitatis Scientiarum Budapestinensis de Rolando Eötvös …, 2024 | | 2024 |
| Structural Extensions of Basis Pursuit: Guarantees on Adversarial Robustness D Szeghy, M Aslan, Á Fóthi, B Mészáros, ZÁ Milacski, A Lőrincz arXiv preprint arXiv:2205.08955, 2022 | | 2022 |
| Common Fate Based Episodic Segmentation by Combining Supervoxels with Deep Neural Networks L Kopácsi, Á Fóthi, Á Fodor, E Somfai, A Lőrincz 2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019 | | 2019 |
| A Layered Group Basis Pursuit támadásokkal szembeni stabilitásának vizsgálata D Szeghy, ZÁ Milacski, Á Fóthi, A Lőrincz | | |
Lorincz, AndrasEotvos Lorand UniversityVerified email at inf.elte.hu
