@proceedings {145,
	title = {Variational Bayesian Sequence-to-Sequence Networks for Memory-Efficient Sign Language Translation},
	journal = {International Symposium on Visual Computing},
	year = {2020},
	pages = {251-262},
	publisher = {Springer International Publishing},
	address = {Cham},
	abstract = {Memory-efficient continuous Sign Language Translation is a significant challenge for the development of assisted technologies with real-time applicability for the deaf. In this work, we introduce a paradigm of designing recurrent deep networks whereby the output of the recurrent layer is derived from appropriate arguments from nonparametric statistics. A novel variational Bayesian sequence-to-sequence network architecture is proposed that consists of a) a full Gaussian posterior distribution for data-driven memory compression and b) a nonparametric Indian Buffet Process prior for regularization applied on the Gated Recurrent Unit non-gate weights. We dub our approach Stick-Breaking Recurrent network and show that it can achieve a substantial weight compression without diminishing modeling performance.},
	isbn = {978-3-030-64559-5},
	author = {Partaourides, Harris and Voskou, Andreas and Kosmopoulos, Dimitrios and Chatzis, Sotirios and N. Metaxas, Dimitris}
}
@article {14,
	title = {Visual Workflow Recognition Using a Variational Bayesian Treatment of Multistream Fused Hidden Markov Models},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {22},
	year = {2012},
	month = {July},
	pages = {1076 -1086},
	keywords = {active learning-based visual workflow recognition, Bayes methods, classification variance, data labeling, hidden Markov models, image sequences, learned model, learning (artificial intelligence), maximum a posteriori training, maximum information gain method, maximum likelihood training, MFHMM parameters, model variance, multistream fused hidden Markov models, overfitting issues, point estimate-based methods, posterior distribution, training methods, unlabeled data, variational Bayesian treatment, video streaming, video surveillance},
	issn = {1051-8215},
	doi = {10.1109/TCSVT.2012.2189795},
	author = {Sotirios P. Chatzis and D. Kosmopoulos}
}
@article {24,
	title = {A variational Bayesian methodology for hidden Markov models utilizing Student{\textquoteright}s-t mixtures},
	journal = {Pattern Recognition},
	volume = {44},
	year = {2011},
	pages = {295 - 306},
	keywords = {Violence detection},
	issn = {0031-3203},
	doi = {10.1016/j.patcog.2010.09.001},
	author = {Sotirios P. Chatzis and D. Kosmopoulos}
}
@proceedings {18,
	title = {Video summarization guiding evaluative rectification for industrial activity recognition},
	journal = {Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on},
	year = {2011},
	month = {nov.},
	pages = {950-957},
	keywords = {activity recognition framework, evaluative rectification method, feature extraction, image recognition, industrial activity recognition, industrial surveillance video, key-frame extraction, neural nets, neural network, production engineering computing, video signal processing, video summarization},
	doi = {10.1109/ICCVW.2011.6130354},
	author = {Voulodimos, A.S. and Doulamis, A.D. and D. Kosmopoulos and Varvarigou, T.A.}
}
@article {27,
	title = {Vision-based production of personalized video},
	journal = {Signal Processing: Image Communication},
	volume = {24},
	year = {2009},
	pages = {158 - 176},
	keywords = {Automated content production, Human identification, tracking},
	issn = {0923-5965},
	doi = {10.1016/j.image.2008.12.010},
	author = {D.I. Kosmopoulos and A. Doulamis and Makris, A. and N. Doulamis and Sotirios P. Chatzis and S.E. Middleton}
}
@conference {85,
	title = {Violence content classification using audio features},
	booktitle = {Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence},
	year = {2006},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = {Berlin, Heidelberg},
	isbn = {3-540-34117-X, 978-3-540-34117-8},
	author = {Giannakopoulos, Theodoros and Kosmopoulos, Dimitrios and Aristidou, Andreas and Theodoridis, Sergios}
}
