Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Athanasia Zlatintsi"'
Autor:
Athanasia Zlatintsi, Panagiotis P. Filntisis, Niki Efthymiou, Christos Garoufis, George Retsinas, Thomas Sounapoglou, Ilias Maglogiannis, Panayiotis Tsanakas, Nikolaos Smyrnis, Petros Maragos
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 641-651 (2024)
This paper presents an overview of the e-Prevention: Person Identification and Relapse Detection Challenge, which was an open call for researchers at ICASSP-2023. The challenge aimed at the analysis and processing of long-term continuous recordings o
Externí odkaz:
https://doaj.org/article/ac7f0b06f1a045adb26b40e7f8ddba4a
Autor:
Emmanouil Kalisperakis, Thomas Karantinos, Marina Lazaridi, Vasiliki Garyfalli, Panagiotis P. Filntisis, Athanasia Zlatintsi, Niki Efthymiou, Asimakis Mantas, Leonidas Mantonakis, Theodoros Mougiakos, Ilias Maglogiannis, Panayotis Tsanakas, Petros Maragos, Nikolaos Smyrnis
Publikováno v:
Frontiers in Psychiatry, Vol 14 (2023)
IntroductionMonitoring biometric data using smartwatches (digital phenotypes) provides a novel approach for quantifying behavior in patients with psychiatric disorders. We tested whether such digital phenotypes predict changes in psychopathology of p
Externí odkaz:
https://doaj.org/article/59f257100e3e48e683b034249cb123f7
Autor:
Athanasia Zlatintsi, Panagiotis P. Filntisis, Christos Garoufis, Niki Efthymiou, Petros Maragos, Andreas Menychtas, Ilias Maglogiannis, Panayiotis Tsanakas, Thomas Sounapoglou, Emmanouil Kalisperakis, Thomas Karantinos, Marina Lazaridi, Vasiliki Garyfalli, Asimakis Mantas, Leonidas Mantonakis, Nikolaos Smyrnis
Publikováno v:
Sensors, Vol 22, Iss 19, p 7544 (2022)
Wearable technologies and digital phenotyping foster unique opportunities for designing novel intelligent electronic services that can address various well-being issues in patients with mental disorders (i.e., schizophrenia and bipolar disorder), thu
Externí odkaz:
https://doaj.org/article/a127b11c177645cf911785a69f35c8c6
Autor:
Athanasia Zlatintsi, Petros Koutras, Georgios Evangelopoulos, Nikolaos Malandrakis, Niki Efthymiou, Katerina Pastra, Alexandros Potamianos, Petros Maragos
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2017, Iss 1, Pp 1-24 (2017)
Abstract Research related to computational modeling for machine-based understanding requires ground truth data for training, content analysis, and evaluation. In this paper, we present a multimodal video database, namely COGNIMUSE, annotated with sen
Externí odkaz:
https://doaj.org/article/8227720ba6b24450ae51c338d8c28908
Autor:
Nikolaos Smyrnis, Emmanouil Kalipserakis, Thomas karantinos, Marina Lazaridi, Vasiliki Garyfali, Panagiotis Filntisis, Athanasia Zlatintsi, Niki Efthymiou, Asimakis Mantas, Leonidas Mantonakis, Theodoros Mougiakos, Ilias Maglogiannis, Panayiotis Tsanakas, Petros Maragos
IntroductionMonitoring biometric data using smartwatches (digital phenotypes) provides a novel approach for quantifying behavior in patients with psychiatric disorders. We tested whether such digital phenotypes predict changes in psychopathology of p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e9465651bb081eeb72eb188b98da5d2
https://doi.org/10.21203/rs.3.rs-1803398/v1
https://doi.org/10.21203/rs.3.rs-1803398/v1
Autor:
Manuel Bouillon, Carlos Acosta, Kosmas Kritsis, Robert Piéchaud, Christos Garoufis, Vassilis Katsouros, Daniel Martín-Albo, Athanasia Zlatintsi, Petross Marago
Publikováno v:
Journal of the Audio Engineering Society. 68:738-746
Autor:
E. Kalisperakis, T. Karantinos, Athanasia Zlatintsi, Christos Garoufis, Niki Efthymiou, Nikolaos Smyrnis, V. Garyfalli, Petros Maragos, L. Mantonakis, Panagiotis Paraskevas Filntisis
Publikováno v:
BHI
In this work, we aim to explore and develop a speech analysis system that identifies relapses in patients with psychotic disorders (i.e., bipolar disorder and schizophrenia) with the long-term goal of monitoring and detecting relapse indicators, in o
Autor:
Athanasia Zlatintsi, Christos Garoufis, Agelos Kratimenos, Petros Maragos, Kleanthis Avramidis
Publikováno v:
ICASSP
Sound Event Detection and Audio Classification tasks are traditionally addressed through time-frequency representations of audio signals such as spectrograms. However, the emergence of deep neural networks as efficient feature extractors has enabled
The advent of deep learning has led to the prevalence of deep neural network architectures for monaural music source separation, with end-to-end approaches that operate directly on the waveform level increasingly receiving research attention. Among t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc918aee35587b791d5d09a8ea49e713
http://arxiv.org/abs/2103.04336
http://arxiv.org/abs/2103.04336
Autor:
Agelos Kratimenos, Kleanthis Avramidis, Athanasia Zlatintsi, Petros Maragos, Christos Garoufis
Publikováno v:
EUSIPCO
Instrument classification is one of the fields in Music Information Retrieval (MIR) that has attracted a lot of research interest. However, the majority of that is dealing with monophonic music, while efforts on polyphonic material mainly focus on pr