@article {156,
	title = {Context-Aware Automatic Sign Language Video Transcription in Psychiatric Interviews},
	journal = {Sensors},
	volume = {22},
	year = {2022},
	pages = {2656},
	abstract = {<span>Sign language (SL) translation constitutes an extremely challenging task when undertaken in a general unconstrained setup, especially in the absence of vast training datasets that enable the use of end-to-end solutions employing deep architectures. In such cases, the ability to incorporate prior information can yield a significant improvement in the translation results by greatly restricting the search space of the potential solutions. In this work, we treat the translation problem in the limited confines of psychiatric interviews involving doctor-patient diagnostic sessions for deaf and hard of hearing patients with mental health problems.To overcome the lack of extensive training data and be able to improve the obtained translation performance, we follow a domain-specific approach combining data-driven feature extraction with the incorporation of prior information drawn from the available domain knowledge. This knowledge enables us to model the context of the interviews by using an appropriately defined hierarchical ontology for the contained dialogue, allowing for the classification of the current state of the interview, based on the doctor{\textquoteright}s question. Utilizing this information, video transcription is treated as a sentence retrieval problem. The goal is predicting the patient{\textquoteright}s sentence that has been signed in the SL video based on the available pool of possible responses, given the context of the current exchange. Our experimental evaluation using simulated scenarios of psychiatric interviews demonstrate the significant gains of incorporating context awareness in the system{\textquoteright}s decisions.</span>},
	author = {Erion-Vasilis Pikoulis and Aristeidis Bifis and Maria Trigka and Constantinos Constantinopoulos and Dimitrios Kosmopoulos}
}
@inbook {124,
	title = {Plant Leaf Recognition Using Zernike Moments and Histogram of Oriented Gradients},
	booktitle = {Artificial Intelligence: Methods and Applications},
	series = {Lecture Notes in Computer Science},
	volume = {8445},
	year = {2014},
	pages = {406-417},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	abstract = {A method using Zernike Moments and Histogram of Oriented Gradients for classification of plant leaf images is proposed in this paper. After preprocessing, we compute the shape features of a leaf using Zernike Moments and texture features using Histogram of Oriented Gradients and then the Sup-port Vector Machine classifier is used for plant leaf image classification and recognition. Experimental results show that using both Zernike Moments and Histogram of Oriented Gradients to classify and recognize plant leaf image yields accuracy that is comparable or better than the state of the art. The method has been validated on the Flavia and the Swedish Leaves datasets as well as on a combined dataset.},
	keywords = {Histogram of oriented gradients, Leaf recognition, Support vector machine, Zernike moments},
	isbn = {978-3-319-07063-6},
	doi = {10.1007/978-3-319-07064-3_33},
	url = {http://dx.doi.org/10.1007/978-3-319-07064-3_33},
	author = {Tsolakidis, DimitrisG. and Kosmopoulos, DimitriosI. and Papadourakis, George},
	editor = {Likas, Aristidis and Blekas, Konstantinos and Kalles, Dimitris}
}
@article {31,
	title = {A hierarchical feature fusion framework for adaptive visual tracking},
	journal = {Image and Vision Computing},
	volume = {29},
	year = {2011},
	pages = {594 - 606},
	keywords = {Particle filter, Sequential Monte-Carlo, Visual tracking},
	issn = {0262-8856},
	doi = {10.1016/j.imavis.2011.07.001},
	author = {Alexandros Makris and Dimitrios Kosmopoulos and Stavros Perantonis and Sergios Theodoridis}
}
@article {26,
	title = {Multimodal and ontology-based fusion approaches of audio and visual processing for violence detection in movies},
	journal = {Expert Systems with Applications},
	volume = {38},
	year = {2011},
	pages = {14102 - 14116},
	keywords = {Knowledge representation, Learning, Movie, Multimodal fusion, Ontology, Reasoning, Violence},
	issn = {0957-4174},
	doi = {10.1016/j.eswa.2011.04.219},
	author = {Thanassis Perperis and Theodoros Giannakopoulos and Alexandros Makris and D. Kosmopoulos and Sofia Tsekeridou and Stavros J. Perantonis and Sergios Theodoridis}
}
@conference {101,
	title = {Audio-Visual Fusion for Detecting Violent Scenes in Videos},
	booktitle = {Artificial Intelligence: Theories, Models and Applications, 6th Hellenic Conference on AI, SETN 2010, Athens, Greece, May 4-7, 2010. Proceedings},
	year = {2010},
	publisher = {Springer},
	organization = {Springer},
	author = {Theodoros Giannakopoulos and Alexandros Makris and Dimitrios I. Kosmopoulos and Stavros J. Perantonis and Sergios Theodoridis}
}
@article {17,
	title = {Automated Pressure Ulcer Lesion Diagnosis for Telemedicine Systems},
	journal = {Engineering in Medicine and Biology Magazine, IEEE},
	volume = {26},
	year = {2007},
	month = {Sept.-Oct.},
	pages = {18 -22},
	keywords = {automated pressure ulcer lesion diagnosis, biomedical imaging, diagnostic tools, digital images, image classification, medical diagnostic computing, region classification, remote patient location, telemedicine, telemedicine systems},
	issn = {0739-5175},
	doi = {10.1109/EMB.2007.901786},
	author = {D. Kosmopoulos and Tzevelekou, F.L.}
}
@proceedings {4,
	title = {Hierarchical Feature Fusion for Visual Tracking},
	journal = {IEEE Int Conf on Image Processing},
	year = {2007},
	pages = {289-292},
	author = {Makris, A. and D. Kosmopoulos and Perantonis, S.J. and Theodoridis, S.}
}
@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}
}
