| Arm Gesture Recognition using a Convolutional Neural Network E Mathe, A Mitsou, E Spyrou, P Mylonas 2018 13th International Workshop on Semantic and Social Media Adaptation and …, 2018 | 24 | 2018 |
| Connecting a Consumer Brain-Computer Interface to an Internet-of-Things Ecosystem E Mathe, E Spyrou Proceedings of the 9th ACM International Conference on PErvasive …, 2016 | 21 | 2016 |
| A deep learning approach for human action recognition using skeletal information E Mathe, A Maniatis, E Spyrou, P Mylonas GeNeDis 2018: Computational Biology and Bioinformatics, 105-114, 2020 | 20 | 2020 |
| Recognizing human actions using 3d skeletal information and CNNs A Papadakis, E Mathe, I Vernikos, A Maniatis, E Spyrou, P Mylonas Engineering Applications of Neural Networks: 20th International Conference …, 2019 | 18 | 2019 |
| A Geometric Approach for Cross-View Human Action Recognition using Deep Learning A Papadakis, E Mathe, E Spyrou, P Mylonas 2019 11th International Symposium on Image and Signal Processing and …, 2019 | 16 | 2019 |
| Domain-Specific Term Extraction: A Case Study on Greek Maritime Legal Texts D Mouratidis, E Mathe, Y Voutos, K Stamou, KL Kermanidis, P Mylonas, ... Proceedings of the 12th Hellenic Conference on Artificial Intelligence, 1-6, 2022 | 11 | 2022 |
| An image representation of skeletal data for action recognition using convolutional neural networks. I Vernikos, E Mathe, A Papadakis, E Spyrou, P Mylonas PETRA, 325-326, 2019 | 11 | 2019 |
| Data Augmentation vs. Domain Adaptation—A Case Study in Human Activity Recognition E Spyrou, E Mathe, G Pikramenos, K Kechagias, P Mylonas Technologies 8 (4), 55, 2020 | 10 | 2020 |
| Fusing Handcrafted and Contextual Features for Human Activity Recognition I Vernikos, E Mathe, E Spyrou, A Mitsou, T Giannakopoulos, P Mylonas 2019 14th International Workshop on Semantic and Social Media Adaptation and …, 2019 | 10 | 2019 |
| A multimodal fusion approach for human activity recognition D Koutrintzes, E Spyrou, E Mathe, P Mylonas International Journal of Neural Systems 33 (01), 2350002, 2023 | 9 | 2023 |
| Assessment of user experience with a commercial BCI device E Mathe, E Spyrou Proc. Hellenic Conf. Electrical and Computer Engineering Students, 2015 | 9 | 2015 |
| Boosting the Performance of Deep Approaches through Fusion with Handcrafted Features. D Koutrintzes, E Mathe, E Spyrou ICPRAM, 370-377, 2022 | 6 | 2022 |
| A study on the Effect of Occlusion in Human Activity Recognition I Giannakos, E Mathe, E Spyrou, P Mylonas Proceedings of the 14th PErvasive Technologies Related to Assistive …, 2021 | 6 | 2021 |
| An adversarial semi-supervised approach for action recognition from pose information G Pikramenos, E Mathe, E Vali, I Vernikos, A Papadakis, E Spyrou, ... Neural Computing and Applications 32, 17181-17195, 2020 | 6 | 2020 |
| A novel CNN-LSTM hybrid architecture for the recognition of human activities S Stylianou-Nikolaidou, I Vernikos, E Mathe, E Spyrou, P Mylonas International Conference on Engineering Applications of Neural Networks, 121-132, 2021 | 5 | 2021 |
| Early Fusion of Visual Representations of Skeletal Data for Human Activity Recognition I Vernikos, D Koutrintzes, E Mathe, E Spyrou, P Mylonas Proceedings of the 12th Hellenic Conference on Artificial Intelligence, 1-5, 2022 | 4 | 2022 |
| Human activity recognition under partial occlusion IA Kostis, E Mathe, E Spyrou, P Mylonas International Conference on Engineering Applications of Neural Networks, 297-309, 2022 | 3 | 2022 |
| User evaluation of low-cost, non-invasive methods for heart-rate measurement E Mathe, E Spyrou Journal of Usability Studies 15 (3), 145-165, 2020 | 3 | 2020 |
| A deep hybrid architecture for human activity recognition S Stylianou-Nikolaidou, I Vernikos, E Mathe, E Spyrou Proceedings of the 14th PErvasive Technologies Related to Assistive …, 2021 | 2 | 2021 |
| A deep regression approach for human activity recognition under partial occlusion I Vernikos, E Spyrou, IA Kostis, E Mathe, P Mylonas International Journal of Neural Systems 33 (09), 2350047, 2023 | 1 | 2023 |
Evaggelos SpyrouAssociate Professor, Department of Informatics and Telecommunications, University of ThessalyΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα uth.gr
