| Deep neural architectures for prediction in healthcare D Kollias, A Tagaris, A Stafylopatis, S Kollias, G Tagaris Complex & Intelligent Systems 4, 119-131, 2018 | 171 | 2018 |
| Machine learning for neurodegenerative disorder diagnosis—survey of practices and launch of benchmark dataset A Tagaris, D Kollias, A Stafylopatis, G Tagaris, S Kollias International Journal on Artificial Intelligence Tools 27 (03), 1850011, 2018 | 66 | 2018 |
| Adaptation and contextualization of deep neural network models D Kollias, M Yu, A Tagaris, G Leontidis, A Stafylopatis, S Kollias 2017 IEEE symposium series on computational intelligence (SSCI), 1-8, 2017 | 57 | 2017 |
| Assessment of parkinson’s disease based on deep neural networks A Tagaris, D Kollias, A Stafylopatis Engineering Applications of Neural Networks: 18th International Conference …, 2017 | 49 | 2017 |
| On line emotion detection using retrainable deep neural networks D Kollias, A Tagaris, A Stafylopatis 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016 | 43 | 2016 |
| Generative Adversarial Networks as an Advanced Data Augmentation Technique for MRI Data. F Konidaris, T Tagaris, M Sdraka, A Stafylopatis VISIGRAPP (5: VISAPP), 48-59, 2019 | 29 | 2019 |
| From free-text user reviews to product recommendation using paragraph vectors and matrix factorization G Alexandridis, T Tagaris, G Siolas, A Stafylopatis Companion Proceedings of the 2019 World Wide Web Conference, 335-343, 2019 | 25 | 2019 |
| High-resolution class activation mapping T Tagaris, M Sdraka, A Stafylopatis 2019 IEEE international conference on image processing (ICIP), 4514-4518, 2019 | 18 | 2019 |
| Intelligent techniques for anomaly detection in nuclear reactors G Ioannou, T Tagaris, G Alexandridis, A Stafylopatis EPJ web of conferences 247, 21011, 2021 | 12 | 2021 |
| Putting together wavelet-based scaleograms and convolutional neural networks for anomaly detection in nuclear reactors T Tagaris, G Ioannou, M Sdraka, G Alexandridis, A Stafylopatis Proceedings of the 3rd International Conference on Advances in Artificial …, 2019 | 10 | 2019 |
| Multi-task learning for predicting Parkinson's disease based on medical imaging information A Vlachostergiou, A Tagaris, A Stafylopatis, S Kollias 2018 25th IEEE International Conference on Image Processing (ICIP), 2052-2056, 2018 | 9 | 2018 |
| Adalip: An adaptive learning rate method per layer for stochastic optimization G Ioannou, T Tagaris, A Stafylopatis Neural Processing Letters 55 (5), 6311-6338, 2023 | 7 | 2023 |
| Hide-and-seek: A template for explainable AI T Tagaris, A Stafylopatis arXiv preprint arXiv:2005.00130, 2020 | 7 | 2020 |
| Investigating the Best Performing Task Conditions of a Multi-Tasking Learning Model in Healthcare Using Convolutional Neural Networks: Evidence from a Parkinson'S Disease Database A Vlachostergiou, A Tagaris, A Stafylopatis, S Kollias 2018 25th IEEE International Conference on Image Processing (ICIP), 2047-2051, 2018 | 6 | 2018 |
| Andreas Stafylopatis και Stefanos Kollias D Kollias, M Yu, A Tagaris, G Leontidis Adaptation and contextualization of deep neural network models. 2017 IEEE …, 0 | 5 | |
| Visual interpretability analysis of Deep CNNs using an Adaptive Threshold method on Diabetic Retinopathy images G Ioannou, T Papagiannis, T Tagaris, G Alexandridis, A Stafylopatis Proceedings of the IEEE/CVF International Conference on Computer Vision, 480-486, 2021 | 4 | 2021 |
| Improving the convergence speed of deep neural networks with biased sampling G Ioannou, T Tagaris, A Stafylopatis Proceedings of the 3rd International Conference on Advances in Artificial …, 2019 | 3 | 2019 |
| Advancing the terminological classification of semi-structured documents G Stratogiannis, G Siolas, G Stamou, A Stafylopatis, A Chortaras, ... 2015 IEEE 27th international conference on tools with artificial …, 2015 | 1 | 2015 |
