Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Matthew, Pediaditis"'
Autor:
Anastasia Pampouchidou, Matthew Pediaditis, Anna Maridaki, Muhammad Awais, Calliope-Marina Vazakopoulou, Stelios Sfakianakis, Manolis Tsiknakis, Panagiotis Simos, Kostas Marias, Fan Yang, Fabrice Meriaudeau
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2017, Iss 1, Pp 1-11 (2017)
Abstract Depression is the most prevalent mood disorder and a leading cause of disability worldwide. Automated video-based analyses may afford objective measures to support clinical judgments. In the present paper, categorical depression assessment i
Externí odkaz:
https://doaj.org/article/9482022385124d0386431871febd624e
Autor:
Maria Samara, Cristina Farmaki, Nikolaos Zacharioudakis, Matthew Pediaditis, Myrto Krana, Vangelis Sakkalis
Publikováno v:
2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE).
Autor:
Matthew Pediaditis, Cristina Farmaki, Sophia Schiza, Nikolaos Tzanakis, Emmanouil Galanakis, Vangelis Sakkalis
Publikováno v:
2022 IEEE International Conference on Imaging Systems and Techniques (IST).
Autor:
Cristina Farmaki, Nikolaos Zacharioudakis, Matthew Pediaditis, Myrto Krana, Vangelis Sakkalis
Publikováno v:
2022 IEEE International Conference on Imaging Systems and Techniques (IST).
Autor:
Marios Antonakakis, Konstantinos Politof, Georgios A. Klados, Glykeria Sdoukopoulou, Sophia Schiza, Maria Panadogiorgaki, Christina Farmaki, Matthew Pediaditis, Michalis E. Zervakis, Vangelis Sakkalis
Publikováno v:
2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE).
Autor:
Kostas Marias, Fan Yang, Manolis Tsiknakis, Anastasia Pampouchidou, Panagiotis G. Simos, Matthew Pediaditis, Fabrice Meriaudeau
Publikováno v:
IEEE Transactions on Affective Computing
IEEE Transactions on Affective Computing, 2017, pp.1-1. 〈10.1109/TAFFC.2017.2724035〉
IEEE Transactions on Affective Computing, Institute of Electrical and Electronics Engineers, 2019, 10 (4), pp.445-470. ⟨10.1109/TAFFC.2017.2724035⟩
IEEE Transactions on Affective Computing, 2019, 10 (4), pp.445-470. ⟨10.1109/TAFFC.2017.2724035⟩
IEEE Transactions on Affective Computing, 2017, pp.1-1. 〈10.1109/TAFFC.2017.2724035〉
IEEE Transactions on Affective Computing, Institute of Electrical and Electronics Engineers, 2019, 10 (4), pp.445-470. ⟨10.1109/TAFFC.2017.2724035⟩
IEEE Transactions on Affective Computing, 2019, 10 (4), pp.445-470. ⟨10.1109/TAFFC.2017.2724035⟩
International audience; Automatic depression assessment based on visual cues is a rapidly growing research domain. The present exhaustive review of existing approaches as reported in over sixty publications during the last ten years focuses on image
Autor:
Matthew, Pediaditis, Anca-Nicoleta, Ciubotaru, Thomas, Brunschwiler, Peter, Hilfiker, Thomas, Grunwald, Marcellina, Ha Berlin, Lukas, Imbach, Carl, Muroi, Christian, Stra Ssle, Emanuela, Keller, Maria, Gabrani
Publikováno v:
AMIA Annu Symp Proc
Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan i
Publikováno v:
ICHI
Human behavior is influenced by numerous subjective factors such as the environment, culture, hormones, genes etc. This makes the development of a one-size-fits-all behavioral model for emotion recognition challenging, especially in the domain of aff
Autor:
Anastasia Pampouchidou, Kostas Marias, Panagiotis G. Simos, Fan Yang, Dimitris Manousos, Stelios Sfakianakis, Manolis Tsiknakis, Matthew Pediaditis, Alexandros N. Vgontzas, Fabrice Meriaudeau, Maria Basta, Eleni Kazantzaki, K. Argyraki, I. A. Apostolaki
Publikováno v:
Machine Vision and Applications. 31
There is a growing interest in computational approaches permitting accurate detection of nonverbal signs of depression and related symptoms (i.e., anxiety and distress) that may serve as minimally intrusive means of monitoring illness progression. Th
Autor:
Dimitris Manousos, Kostas Marias, Matthew Pediaditis, Panagiotis G. Simos, Eleni Kazantzaki, Franco Chiarugi, Giorgos Giannakakis, Manolis Tsiknakis
Publikováno v:
Biomedical Signal Processing and Control. 31:89-101
This study develops a framework for the detection and analysis of stress/anxiety emotional states through video-recorded facial cues. A thorough experimental protocol was established to induce systematic variability in affective states (neutral, rela