V
Vasiliki Kosmidou
Researcher at Information Technology Institute
Publications - 31
Citations - 730
Vasiliki Kosmidou is an academic researcher from Information Technology Institute. The author has contributed to research in topics: Electroencephalography & Gesture recognition. The author has an hindex of 13, co-authored 28 publications receiving 607 citations. Previous affiliations of Vasiliki Kosmidou include Aristotle University of Thessaloniki.
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Journal ArticleDOI
Sign Language Recognition Using Intrinsic-Mode Sample Entropy on sEMG and Accelerometer Data
TL;DR: Experimental results from the IMEn analysis applied to GSL signs corresponding to 60-word lexicon repeated ten times by three native signers have shown more than 93% mean classification accuracy using IMEn as the only source of the classification feature set.
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Using landscape structure to develop quantitative baselines for protected area monitoring
Paola Mairota,Barbara Cafarelli,Luigi Boccaccio,Vincenzo Leronni,Rocco Labadessa,Vasiliki Kosmidou,Harini Nagendra +6 more
TL;DR: The framework developed has significant potential to capture information on major landscape structural features, identify problematic areas of increased fragmentation that can be used to prioritise research, monitoring and intervention, and provide early warning signals for immediate response to pressures increasing habitat fragmentation.
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The Earth Observation Data for Habitat Monitoring (EODHaM) System
Richard Lucas,Palma Blonda,Peter Bunting,Gwawr Angharad Jones,Jordi Inglada,Marcela Arias,Vasiliki Kosmidou,Zisis I. Petrou,Ioannis Manakos,Maria Adamo,Rebecca Charnock,Cristina Tarantino,Caspar A. Mücher,Rob H. G. Jongman,Henk Kramer,Damien Arvor,João P. Honrado,Paola Mairota +17 more
TL;DR: The EODHaM approach has adopted the Food and Agriculture Organization Land Cover Classification System (LCCS) taxonomy and translates mapped classes to General Habitat Categories (GHCs) from which Annex I habitats (EU Habitats Directive) can be defined.
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Electroencephalogram and Alzheimer's disease: clinical and research approaches.
TL;DR: This review tried to focus on the main research fields of AD via EEG and recent published studies to form a knowledge platform for the project entitled “Cognitive Signal Processing Lab,” which is in progress in Information Technology Institute in Thessaloniki.
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Brain source localization of MMN, P300 and N400: aging and gender differences.
Anthoula Tsolaki,Vasiliki Kosmidou,Leontios J. Hadjileontiadis,Ioannis Kompatsiaris,Magda Tsolaki +4 more
TL;DR: The enhanced potential of HD-EEG data is justified to accurately reflect the age and gender dependencies at the three components of simple auditory ERPs and pave the way for the investigation of neurodegenerative pathologies, such as the Alzheimer's disease.