Michalis Papakostas
Michalis Papakostas
Research Scientist, GN Advanced Science
Verified email at - Homepage
Cited by
Cited by
Deep visual attributes vs. hand-crafted audio features on multidomain speech emotion recognition
M Papakostas, E Spyrou, T Giannakopoulos, G Siantikos, ...
Computation 5 (2), 26, 2017
Speech-music discrimination using deep visual feature extractors
M Papakostas, T Giannakopoulos
Expert Systems with Applications 114, 334-344, 2018
Grounding the meaning of words through vision and interactive gameplay
N Parde, A Hair, M Papakostas, K Tsiakas, M Dagioglou, V Karkaletsis, ...
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
Cognilearn: A deep learning-based interface for cognitive behavior assessment
S Gattupalli, D Ebert, M Papakostas, F Makedon, V Athitsos
Proceedings of the 22nd International Conference on Intelligent User …, 2017
Physical fatigue detection through EMG wearables and subjective user reports: a machine learning approach towards adaptive rehabilitation
M Papakostas, V Kanal, M Abujelala, K Tsiakas, F Makedon
Proceedings of the 12th ACM international conference on pervasive …, 2019
A survey of assistive technologies for assessment and rehabilitation of motor impairments in multiple sclerosis
A Rajavenkatanarayanan, V Kanal, K Tsiakas, D Calderon, M Papakostas, ...
Multimodal Technologies and Interaction 3 (1), 6, 2019
Short-term recognition of human activities using convolutional neural networks
M Papakostas, T Giannakopoulos, F Makedon, V Karkaletsis
2016 12th international conference on signal-image technology & internet …, 2016
Towards predicting task performance from EEG signals
M Papakostas, K Tsiakas, T Giannakopoulos, F Makedon
2017 IEEE International Conference on Big Data (Big Data), 4423-4425, 2017
Recognizing emotional states using speech information
M Papakostas, G Siantikos, T Giannakopoulos, E Spyrou, ...
GeNeDis 2016: Geriatrics, 155-164, 2017
An interactive multisensing framework for personalized human robot collaboration and assistive training using reinforcement learning
K Tsiakas, M Papakostas, M Theofanidis, M Bell, R Mihalcea, S Wang, ...
Proceedings of the 10th International Conference on PErvasive Technologies …, 2017
Monitoring breathing activity and sleep patterns using multimodal non-invasive technologies
M Papakostas, J Staud, F Makedon, V Metsis
Proceedings of the 8th ACM International Conference on PErvasive …, 2015
Cogbeacon: A multi-modal dataset and data-collection platform for modeling cognitive fatigue
M Papakostas, A Rajavenkatanarayanan, F Makedon
Technologies 7 (2), 46, 2019
Towards detecting levels of alertness in drivers using multiple modalities
K Riani, M Papakostas, H Kokash, M Abouelenien, M Burzo, R Mihalcea
Proceedings of the 13th ACM International Conference on PErvasive …, 2020
Towards designing a socially assistive robot for adaptive and personalized cognitive training
K Tsiakas, C Abellanoza, M Abujelala, M Papakostas, T Makada, ...
Proceedings of the Robots 4, 2017
An interactive learning and adaptation framework for adaptive robot assisted therapy
K Tsiakas, M Papakostas, B Chebaa, D Ebert, V Karkaletsis, F Makedon
Proceedings of the 9th ACM International Conference on PErvasive …, 2016
A Deep Learning Approach Towards Multimodal Stress Detection.
CP Bara, M Papakostas, R Mihalcea
AffCon@ AAAI, 67-81, 2020
Muser: Multimodal stress detection using emotion recognition as an auxiliary task
Y Yao, M Papakostas, M Burzo, M Abouelenien, R Mihalcea
arXiv preprint arXiv:2105.08146, 2021
A survey of sensing modalities for human activity, behavior, and physiological monitoring
A Lioulemes, M Papakostas, SN Gieser, T Toutountzi, M Abujelala, ...
Proceedings of the 9th ACM International Conference on PErvasive …, 2016
Extracting emotions from speech using a bag-of-visual-words approach
E Spyrou, T Giannakopoulos, D Sgouropoulos, M Papakostas
2017 12th International Workshop on Semantic and Social Media Adaptation and …, 2017
Distracted and drowsy driving modeling using deep physiological representations and multitask learning
M Papakostas, K Das, M Abouelenien, R Mihalcea, M Burzo
Applied Sciences 11 (1), 88, 2020
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