@article {164,
	title = {A Multispectral Dataset for the Detection of Tuta absoluta and Leveillula taurica in Tomato Plants},
	journal = {Smart Agricultural Technology},
	year = {2022},
	pages = {100146},
	abstract = {Tomato (Solanum lycopersicum) is one of the most important vegetables for human nutrition and its cultivation employs amounts of resources worldwide. However, tomato cultivation is plagued by several diseases and pests that increase production cost and introduce additional environmental and health risks due to pesticide use. Timely disease and pest detection is of high importance for tomato crop output and the environment, since plant protection input can be optimized. Here, we present a dataset of multispectral images (RGB and NIR) of tomato plants, at various stages of infection with Tuta absoluta and Leveillula taurica, which to our knowledge is unique. The dataset comprised of 263 images collected from a real greenhouse. Additionally, we applied a baseline Faster-RCNN object detector for the localization and classification lesions. Our experiments include (i) a version for the RGB channels and (ii) a custom backbone architecture version for feature fusion using the same Faster-RCNN head. Lastly, based on the detector{\textquoteright}s output, we compute an \&gt;0.9 F1-score on binary classification, while mAP 18.5\% and mAP 20.2\% on detection, highlight the added value of NIR spectral bands for detecting these diseases.},
	keywords = {Faster-RCNN, Feature fusion, Leaf Miner, Plant Disease Dataset, Powdery Mildew},
	issn = {2772-3755},
	doi = {https://doi.org/10.1016/j.atech.2022.100146},
	url = {https://www.sciencedirect.com/science/article/pii/S2772375522001101},
	author = {P.S. Georgantopoulos and D. Papadimitriou and C. Constantinopoulos and T. Manios and I.N. Daliakopoulos and D. Kosmopoulos}
}
@proceedings {147,
	title = {A Method for Recovering Near Infrared Information from RGB Measurements with Application in Precision Agriculture},
	journal = {European Signal Processing Conference},
	year = {2021},
	pages = {616-620},
	publisher = {IEEE},
	edition = {IEEE},
	abstract = {[size= 13.008px]In this work we develop a cost-efficient coupled dictionary learning based method for reconstructing multispectral images using only a single RGB commercial camera, without requiring the sensitivity function of the camera sensor. Considering the very high cost, the acquisition time and reduced mobility of multispectral cameras we claim that this is a very attractive option. In contrast to other approaches, the proposed method is not limited only to spectral bands inside the visible spectrum, but it also considers an even more challenging task, that is the reconstruction of spectral bands outside the visible range closer to the near-infrared wavelengths of the spectrum. Extensive experiments with real data demonstrate the effectiveness and applicability of the proposed method in the precision agriculture domain. To this end, we calculate one of the most widely used vegetation indices, the normalized difference vegetation index (NVDI), which may be used for plant health monitoring.[/size]},
	author = {A. Gkillas and D. Kosmopoulos and C. Constantinopoulos and D. Ampeliotis and K. Berberidis}
}
@proceedings {135,
	title = {A Dataset of Mycenaean Linear B Sequences},
	journal = {Language Resources and Evaluation Conference - LREC},
	year = {2020},
	pages = {2552-2561},
	abstract = {[size= 13.008px]We present a dataset of Mycenaean Linear B sequences gathered from the Mycenaean inscriptions written in the 13th and 14th century B.C. (c. 1400-1200 B.C.). The dataset contains sequences of Mycenaean words and ideograms according to the rules of the Mycenaean Greek language in the Late Bronze Age. Our ultimate goal is to contribute to the study, reading and understanding of ancient scripts and languages. Focusing on sequences, we seek to exploit the structure of the entire language, not just the Mycenaean vocabulary, to analyse sequential patterns. We present an initial experiment on estimating the missing symbols in damaged inscriptions using the dataset.[/size]},
	author = {K. Papavasileiou and G. Owens and D. Kosmopoulos}
}
@proceedings {134,
	title = {Towards a visual Sign Language dataset for home care services},
	journal = {15th IEEE International Conference on Face and Gesture Recognition},
	volume = {1},
	year = {2020},
	month = {2020},
	pages = {622-626},
	abstract = {[size= 13.008px]We present our work towards creating a dataset, which is intended to be used for the implementation of a home care services system for the deaf. The dataset includes recorded realistic scenarios of interactions between deaf patients and mental health experts in their native sign language. The scenarios allow for contextualized representations, in contrast to typical datasets presenting isolated signs or sentences. It includes continuous videos in RGB and depth, which are challenging to analyze and closely resemble real-life scenarios. The research on representation of signs is supported by providing the hand shapes and trajectories for every video using hand and skeleton models, as well as facial features. Furthermore, the dataset may be used for the study of emotional context in Sign Language, since such conversations are typically emotionally charged. [/size]},
	author = {D. Kosmopoulos and I. Oikonomidis and K. Konstantinopoulos and N. Arvanitis and K. Antzakas and A. Bifis and G. Lydakis and A. Roussos and A. Argyros}
}
@proceedings {133,
	title = {Translation of Sign Language Glosses to Text Using Sequence-to-Sequence Attention Models},
	journal = {The 15th International Conference on Signal Image Technology \& Internet based Systems - SITIS},
	year = {2019},
	month = {2019},
	abstract = {This work deals with the problem of Sign Language Translation and more specifically with translating Glosses to text. We applied Sequence to Sequence models with attention mechanism to a parallel gloss to English corpus. This is the first work that used these models to translate American gloss sentences to English. We present our experiments on several network architectures with three different attention functions. The results are very promising and can be useful for the further implementation of a full sign language recognition system.},
	author = {N. Arvanitis and C. Constantinopoulos and D. Kosmopoulos}
}
@article {38,
	title = {A Conditional Random Field-Based Model for Joint Sequence Segmentation and Classification},
	journal = {Pattern Recognition},
	volume = {46},
	year = {2013},
	month = {06/2013},
	pages = {1569-1578},
	author = {Sotirios P. Chatzis and D. Kosmopoulos and P. Doliotis}
}
@article {11,
	title = {A system for multi-camera task recognition and summarization for structured environments},
	journal = {Industrial Informatics, IEEE Transactions on},
	volume = {9},
	year = {2013},
	pages = {161-171},
	issn = {1551-3203},
	doi = {10.1109/TII.2012.2212712},
	author = {D. Kosmopoulos and A. Voulodimos and Doulamis, A.D.}
}
@article {2,
	title = {Bayesian Filter based Behavior Recognition in Workflows allowing for User Feedback},
	journal = {Computer Vision and Image Understanding},
	volume = {116},
	year = {2012},
	pages = {422-434},
	abstract = {In this paper, we propose a novel online framework for behavior understanding, in visual workflows, capable of achieving high recognition rates in real-time. To effect online recognition, we propose a methodology that employs a Bayesian filter supported by hidden Markov models. We also introduce a novel re-adjustment framework of behavior recognition and classification by incorporating the user{\textquoteright}s feedback into the learning process through two proposed schemes: a plain non-linear one and a more sophisticated recursive one. The proposed approach aims at dynamically correcting erroneous classification results to enhance the behavior modeling and therefore the overall classification rates. The performance is thoroughly evaluated under real-life complex visual behavior understanding scenarios in an industrial plant. The obtained results are compared and discussed. },
	author = {D. Kosmopoulos and N. Doulamis and A. Voulodimos}
}
@article {21,
	title = {A Threefold Dataset for Activity and Workflow Recognition in Complex Industrial Environments},
	journal = {MultiMedia, IEEE},
	volume = {19},
	year = {2012},
	month = {July-Sept.},
	pages = {42 -52},
	issn = {1070-986X},
	doi = {10.1109/MMUL.2012.31},
	author = {Athanasios Voulodimos and D. Kosmopoulos and Vasileiou, Georgios and Sardis, Emmanuel and Anagnostopoulos, Vasileios and Lalos, Constantinos and Doulamis, A.D. and Varvarigou, T.A.}
}
@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}
}
@proceedings {10,
	title = {A Dataset for Workflow Recognition in Industrial Scenes},
	journal = {IEEE International Conference on Image Processing},
	year = {2011},
	pages = {3310-3313},
	author = {A. Voulodimos and D. Kosmopoulos and Vasileiou, G. and Sardis, E. and Doulamis, A.D. and Anagnostopoulos, V. and Lalos, C. and Varvarigou, T.A.}
}
@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}
}
@article {39,
	title = {Multiview Behavior Monitoring for Assistive Environments},
	journal = {Universal Access in the Information Society},
	volume = {10},
	year = {2011},
	pages = {115-123},
	author = {D. Kosmopoulos}
}
@article {9,
	title = {Online classification of visual tasks for industrial workflow monitoring},
	journal = {Neural Networks},
	volume = {24},
	year = {2011},
	pages = {852{\textendash}860},
	keywords = {Activity recognition, ESN, Fusion, Genetic algorithm, HMM, Workflow},
	issn = {0893-6080},
	author = {Athanasios Voulodimos and D. Kosmopoulos and Veres, Galina and Helmut Grabner and Van Gool, Luc and Varvarigou, T.A.}
}
@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.}
}
@proceedings {7,
	title = {Enhanced Human Behavior Recognition using HMM and Evaluative Rectification},
	journal = {ACM Multimedia, ARTEMIS Workshop},
	year = {2010},
	author = {Doulamis, N.D. and Voulodimos, A.S. and D. Kosmopoulos and Varvarigou, T.A.}
}
@proceedings {6,
	title = {Robust human behavior modeling from multiple cameras},
	journal = {Pattern Recognition (ICPR), 20th  International Conference on},
	year = {2010},
	pages = {3575-3578},
	author = {D. Kosmopoulos and Voulodimos, A.S. and Varvarigou, T.A.}
}
@article {5,
	title = {Robust Visual Behavior Recognition},
	journal = {Signal Processing Magazine, IEEE},
	volume = {27},
	year = {2010},
	month = {Sep.},
	pages = {34-45},
	issn = {1053-5888},
	author = {D. Kosmopoulos and Sotirios P. Chatzis}
}
@proceedings {8,
	title = {Robust Workflow Recognition Using Holistic Features and Outlier-Tolerant Fused Hidden Markov Models},
	journal = {International Conference on Artificial Neural Networks},
	volume = {1},
	year = {2010},
	pages = {551-560},
	author = {Athanasios Voulodimos and Helmut Grabner and D. Kosmopoulos and Van Gool, Luc and Varvarigou, T.A.}
}
@article {3,
	title = {Robust Sequential Data Modeling Using an Outlier Tolerant Hidden Markov Model},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {31},
	year = {2009},
	pages = {1657-1669},
	issn = {0162-8828},
	author = {Sotirios P. Chatzis and D. Kosmopoulos and Varvarigou, T.A.}
}
@proceedings {15,
	title = {A robust approach towards sequential data modeling and its application in automatic gesture recognition},
	journal = {Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on},
	year = {2008},
	month = {April},
	pages = {1937-1940},
	keywords = {automatic gesture recognition, data representation, finite Gaussian mixture model, Gaussian distribution, gesture recognition, hidden Markov model, hidden Markov models, hidden state distribution, maximum likelihood estimation, maximum likelihood framework, parameter estimation, sequential data modeling, student-t mixture model, time series, time series modeling},
	doi = {10.1109/ICASSP.2008.4518015},
	author = {Sotirios P. Chatzis and D. Kosmopoulos and Varvarigou, T.A.}
}
@article {12,
	title = {Signal Modeling and Classification Using a Robust Latent Space Model Based on t Distributions},
	journal = {Signal Processing, IEEE Transactions on},
	volume = {56},
	year = {2008},
	month = {March},
	pages = {949 -963},
	keywords = {Bayes methods, Bayesian inference, factor analysis modeling, inference mechanisms, robust latent space model, signal classification, signal modeling, signal processing, statistical distributions, t distribution, variational inference algorithm},
	issn = {1053-587X},
	doi = {10.1109/TSP.2007.907912},
	author = {Sotirios P. Chatzis and D. Kosmopoulos and Varvarigou, T.A.}
}
@article {22,
	title = {Superquadric Segmentation in Range Images via Fusion of Region and Boundary Information},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {30},
	year = {2008},
	month = {may},
	pages = {781 -795},
	keywords = {Algorithms, Artificial Intelligence, Automated, computer vision, Computer-Assisted, edge detection, game theory, game-theoretic framework, Image Enhancement, Image Interpretation, image segmentation, Imaging, iterative methods, model-based edge detection, multiple object segmentation, Pattern Recognition, Reproducibility of Results, robot vision, Sensitivity and Specificity, Subtraction Technique, superquadric segmentation, Three-Dimensional},
	issn = {0162-8828},
	doi = {10.1109/TPAMI.2007.70736},
	author = {Katsoulas, D.K. and Bastidas, C.C. and D. Kosmopoulos}
}
@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.}
}
@article {36,
	title = {Artificial Intelligence Systems for the Characterization of Digital Images Containing Pigmented Skin Lesions: Applications in the Detection of Malignant Melanoma},
	journal = {Oncology Reports},
	volume = {15},
	year = {2006},
	pages = {1027-1032},
	author = {Maglogiannis, Ilias and D. Kosmopoulos}
}
@proceedings {23,
	title = {Box-like Superquadric Recovery in Range Images by Fusing Region and Boundary Information},
	journal = {Pattern Recognition, 18th International Conference on},
	volume = {1},
	year = {2006},
	pages = {719-722},
	keywords = {box-like superquadric recovery, geometry, image reconstruction, image segmentation, object detection, piled box-like object localization, range imagery, recover-and-select framework, robotic bin-picking problem, superquadric segmentation},
	doi = {10.1109/ICPR.2006.341},
	author = {Katsoulas, D.K. and D. Kosmopoulos}
}
@proceedings {13,
	title = {Content-Based Time Sampling for Efficient Video Delivery over Networks of Low and Variable Bandwidth},
	journal = {Digital Telecommunications, , 2006. ICDT {\textquoteright}06. International Conference on},
	year = {2006},
	month = {Aug.},
	keywords = {bandwidth allocation, computational complexity, content management, content-based time sampling, data compression, decoding, image sampling, image sequences, linear frame skipping method, low bandwidth, MPEG compressed domain, multimedia communication, multimedia information, objective evaluation scheme, variable bandwidth, video coding, video communication, video delivery, video sequences},
	doi = {10.1109/ICDT.2006.26},
	author = {Doulamis, A.D. and D. Kosmopoulos and Doulamis, N.D.}
}
@article {37,
	title = {Hand Tracking for Gesture Recognition Tasks using Dynamic Bayesian Network},
	journal = {International Journal of Intelligent Systems and Applications},
	volume = {1},
	year = {2006},
	pages = {359-375},
	author = {D. Kosmopoulos and Maglogiannis, Ilias}
}
@proceedings {20,
	title = {Content-based decomposition of gesture videos},
	journal = {Signal Processing Systems Design and Implementation, 2005. IEEE Workshop on},
	year = {2005},
	month = {Nov.},
	pages = {319-324},
	keywords = {adapted video summary, binary trees, content-based decomposition, depicted gestures, feature extraction, gesture video decomposition, hierarchically structured video, human computer interaction, human-computer interface applications, key-frame extraction, video browsing, video signal processing, video transmission},
	doi = {10.1109/SIPS.2005.1579886},
	author = {Doulamis, N.D. and Doulamis, A.D. and D. Kosmopoulos}
}
@proceedings {19,
	title = {Gesture-based video summarization},
	journal = {Image Processing, 2005. ICIP 2005. IEEE International Conference on},
	volume = {3},
	year = {2005},
	month = {Sept.},
	pages = {1220-1223},
	keywords = {gesture energy, gesture-based video summarization, gestures extraction, image colour analysis, image segmentation, key-frames extraction, sign language videos, skin color segmentation, visual events, Zernike moments},
	doi = {10.1109/ICIP.2005.1530618},
	author = {D. Kosmopoulos and Doulamis, A.D. and N. Doulamis}
}
@article {25,
	title = {MD-SIR: a methodology for developing sensor{\textemdash}guided industry robots},
	journal = {Robotics and Computer-Integrated Manufacturing},
	volume = {18},
	year = {2002},
	pages = {403 - 419},
	keywords = {Application development, Control objects library, Open robots controller architecture, Sensor integration},
	issn = {0736-5845},
	doi = {10.1016/S0736-5845(02)00031-5},
	author = {D. Kosmopoulos and Varvarigou, T.A. and D.M Emiris and A.A Kostas}
}
@proceedings {16,
	title = {An efficient depalletizing system based on 2D range imagery},
	journal = {Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on},
	volume = {1},
	year = {2001},
	pages = {305-312},
	keywords = {2D range imagery, active vision, depalletizing system, industrial robot, industrial robots, laser beam applications, materials handling, optical tracking, real time systems, real-time systems, time of flight laser sensor, tracking},
	doi = {10.1109/ROBOT.2001.932570},
	author = {Katsoulas, D.K. and D. Kosmopoulos}
}
