Learning Representations of Natural Language Texts with Generative Adversarial Networks at Document, Sentence, and Aspect Level
@article{AILS:journals/algorithms/VlachostergiouC18,
author = {Aggeliki Vlachostergiou and
George Caridakis and
Phivos Mylonas and
Andreas Stafylopatis},
title = {Learning Representations of Natural Language Texts with Generative
Adversarial Networks at Document, Sentence, and Aspect Level},
journal = {Algorithms},
volume = {11},
number = {10},
pages = {164},
year = {2018},
url = {https://doi.org/10.3390/a11100164},
doi = {10.3390/a11100164}
}
author = {Aggeliki Vlachostergiou and
George Caridakis and
Phivos Mylonas and
Andreas Stafylopatis},
title = {Learning Representations of Natural Language Texts with Generative
Adversarial Networks at Document, Sentence, and Aspect Level},
journal = {Algorithms},
volume = {11},
number = {10},
pages = {164},
year = {2018},
url = {https://doi.org/10.3390/a11100164},
doi = {10.3390/a11100164}
}
Deep Bayesian Uncertainty Estimation for Adaptation and Self-Annotation of Food Packaging Images
@article{AILS:journals/corr/abs-1812-01681,
author = {Fabio De Sousa Ribeiro and
Francesco Caliv{\`{a}} and
Mark Swainson and
Kjartan Gudmundsson and
Georgios Leontidis and
Stefanos D. Kollias},
title = {Deep Bayesian Uncertainty Estimation for Adaptation and Self-Annotation
of Food Packaging Images},
journal = {CoRR},
volume = {abs/1812.01681},
year = {2018},
url = {http://arxiv.org/abs/1812.01681},
archivePrefix = {arXiv},
eprint = {1812.01681}
}
author = {Fabio De Sousa Ribeiro and
Francesco Caliv{\`{a}} and
Mark Swainson and
Kjartan Gudmundsson and
Georgios Leontidis and
Stefanos D. Kollias},
title = {Deep Bayesian Uncertainty Estimation for Adaptation and Self-Annotation
of Food Packaging Images},
journal = {CoRR},
volume = {abs/1812.01681},
year = {2018},
url = {http://arxiv.org/abs/1812.01681},
archivePrefix = {arXiv},
eprint = {1812.01681}
}
Towards a Deep Unified Framework for Nuclear Reactor Perturbation Analysis
@article{AILS:journals/corr/abs-1807-10096,
author = {Fabio De Sousa Ribeiro and
Francesco Caliv{\`{a}} and
Dionysios Chionis and
Abdelhamid Dokhane and
Antonios Mylonakis and
Christophe Demazi{\`{e}}re and
Georgios Leontidis and
Stefanos D. Kollias},
title = {Towards a Deep Unified Framework for Nuclear Reactor Perturbation
Analysis},
journal = {CoRR},
volume = {abs/1807.10096},
year = {2018},
url = {http://arxiv.org/abs/1807.10096},
archivePrefix = {arXiv},
eprint = {1807.10096}
}
author = {Fabio De Sousa Ribeiro and
Francesco Caliv{\`{a}} and
Dionysios Chionis and
Abdelhamid Dokhane and
Antonios Mylonakis and
Christophe Demazi{\`{e}}re and
Georgios Leontidis and
Stefanos D. Kollias},
title = {Towards a Deep Unified Framework for Nuclear Reactor Perturbation
Analysis},
journal = {CoRR},
volume = {abs/1807.10096},
year = {2018},
url = {http://arxiv.org/abs/1807.10096},
archivePrefix = {arXiv},
eprint = {1807.10096}
}
Applications of human action analysis and recognition on wireless network infrastructures: State of the art and real world challenges
2018 Innovations in Intelligent Systems and Applications, {INISTA} 2018, Thessaloniki, Greece, July 3-5, 2018, 2018
@inproceedings{AILS:conf/inista/TsatirisKK18,
author = {Georgios Tsatiris and
Kostas Karpouzis and
Stefanos D. Kollias},
title = {Applications of human action analysis and recognition on wireless
network infrastructures: State of the art and real world challenges},
booktitle = {2018 Innovations in Intelligent Systems and Applications, {INISTA}
2018, Thessaloniki, Greece, July 3-5, 2018},
pages = {1--6},
year = {2018},
url = {https://doi.org/10.1109/INISTA.2018.8466317},
doi = {10.1109/INISTA.2018.8466317}
}
author = {Georgios Tsatiris and
Kostas Karpouzis and
Stefanos D. Kollias},
title = {Applications of human action analysis and recognition on wireless
network infrastructures: State of the art and real world challenges},
booktitle = {2018 Innovations in Intelligent Systems and Applications, {INISTA}
2018, Thessaloniki, Greece, July 3-5, 2018},
pages = {1--6},
year = {2018},
url = {https://doi.org/10.1109/INISTA.2018.8466317},
doi = {10.1109/INISTA.2018.8466317}
}
Towards a Deep Unified Framework for Nuclear Reactor Perturbation Analysis
{IEEE} Symposium Series on Computational Intelligence, {SSCI} 2018, Bangalore, India, November 18-21, 2018, 2018
@inproceedings{AILS:conf/ssci/RibeiroCCDMDLK18,
author = {Fabio De Sousa Ribeiro and
Francesco Caliv{\`{a}} and
Dionysios Chionis and
Abdelhamid Dokhane and
Antonios Mylonakis and
Christophe Demazi{\`{e}}re and
Georgios Leontidis and
Stefanos D. Kollias},
title = {Towards a Deep Unified Framework for Nuclear Reactor Perturbation
Analysis},
booktitle = {{IEEE} Symposium Series on Computational Intelligence, {SSCI} 2018,
Bangalore, India, November 18-21, 2018},
pages = {120--127},
year = {2018},
url = {https://doi.org/10.1109/SSCI.2018.8628637},
doi = {10.1109/SSCI.2018.8628637}
}
author = {Fabio De Sousa Ribeiro and
Francesco Caliv{\`{a}} and
Dionysios Chionis and
Abdelhamid Dokhane and
Antonios Mylonakis and
Christophe Demazi{\`{e}}re and
Georgios Leontidis and
Stefanos D. Kollias},
title = {Towards a Deep Unified Framework for Nuclear Reactor Perturbation
Analysis},
booktitle = {{IEEE} Symposium Series on Computational Intelligence, {SSCI} 2018,
Bangalore, India, November 18-21, 2018},
pages = {120--127},
year = {2018},
url = {https://doi.org/10.1109/SSCI.2018.8628637},
doi = {10.1109/SSCI.2018.8628637}
}
A Deep Learning Approach for Load Demand Forecasting of Power Systems
{IEEE} Symposium Series on Computational Intelligence, {SSCI} 2018, Bangalore, India, November 18-21, 2018, 2018
@inproceedings{AILS:conf/ssci/KolliaK18,
author = {Ilianna Kollia and
Stefanos D. Kollias},
title = {A Deep Learning Approach for Load Demand Forecasting of Power Systems},
booktitle = {{IEEE} Symposium Series on Computational Intelligence, {SSCI} 2018,
Bangalore, India, November 18-21, 2018},
pages = {912--919},
year = {2018},
url = {https://doi.org/10.1109/SSCI.2018.8628644},
doi = {10.1109/SSCI.2018.8628644}
}
author = {Ilianna Kollia and
Stefanos D. Kollias},
title = {A Deep Learning Approach for Load Demand Forecasting of Power Systems},
booktitle = {{IEEE} Symposium Series on Computational Intelligence, {SSCI} 2018,
Bangalore, India, November 18-21, 2018},
pages = {912--919},
year = {2018},
url = {https://doi.org/10.1109/SSCI.2018.8628644},
doi = {10.1109/SSCI.2018.8628644}
}
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
2018 {IEEE} International Conference on Image Processing, {ICIP} 2018, Athens, Greece, October 7-10, 2018, 2018
@inproceedings{AILS:conf/icip/VlachostergiouT18,
author = {Aggeliki Vlachostergiou and
Athanasios Tagaris and
Andreas Stafylopatis and
Stefanos D. Kollias},
title = {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},
booktitle = {2018 {IEEE} International Conference on Image Processing, {ICIP} 2018,
Athens, Greece, October 7-10, 2018},
pages = {2047--2051},
year = {2018},
url = {https://doi.org/10.1109/ICIP.2018.8451276},
doi = {10.1109/ICIP.2018.8451276}
}
author = {Aggeliki Vlachostergiou and
Athanasios Tagaris and
Andreas Stafylopatis and
Stefanos D. Kollias},
title = {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},
booktitle = {2018 {IEEE} International Conference on Image Processing, {ICIP} 2018,
Athens, Greece, October 7-10, 2018},
pages = {2047--2051},
year = {2018},
url = {https://doi.org/10.1109/ICIP.2018.8451276},
doi = {10.1109/ICIP.2018.8451276}
}