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pro vyhledávání: '"Garoufis A"'
In this paper, we study whether music source separation can be used as a pre-training strategy for music representation learning, targeted at music classification tasks. To this end, we first pre-train U-Net networks under various music source separa
Externí odkaz:
http://arxiv.org/abs/2310.15845
Contrastive learning constitutes an emerging branch of self-supervised learning that leverages large amounts of unlabeled data, by learning a latent space, where pairs of different views of the same sample are associated. In this paper, we propose mu
Externí odkaz:
http://arxiv.org/abs/2302.07077
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
The study of Music Cognition and neural responses to music has been invaluable in understanding human emotions. Brain signals, though, manifest a highly complex structure that makes processing and retrieving meaningful features challenging, particula
Externí odkaz:
http://arxiv.org/abs/2202.09750
Autor:
Antonia Garypidou, Konstantinos Ypsilantis, Evaggelia Sifnaiou, Maria Manthou, Dimitris Thomos, John C. Plakatouras, Theodoros Tsolis, Achilleas Garoufis
Publikováno v:
Chemistry, Vol 5, Iss 4, Pp 2476-2489 (2023)
Palladium(II) complexes of the general formula [Pd(η3-C3H5)(L)](PF6), where L is 4,7-diphenyl-1,10-phenanthroline (1), 2,9-dimethyl-1,10-phenanthroline (2), 2,9-dimethyl-4,7-diphenyl-1,10-phenanthroline (3), 5-methyl-1,10-phenanthroline (4), 3,4,7,8
Externí odkaz:
https://doaj.org/article/3ef60816ba864d2da392d1dc31f4027a
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:
http://arxiv.org/abs/2103.04336
Autor:
Avramidis, Kleanthis, Kratimenos, Agelos, Garoufis, Christos, Zlatintsi, Athanasia, Maragos, Petros
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
Externí odkaz:
http://arxiv.org/abs/2102.06930
Emotion Recognition from EEG signals has long been researched as it can assist numerous medical and rehabilitative applications. However, their complex and noisy structure has proven to be a serious barrier for traditional modeling methods. In this p
Externí odkaz:
http://arxiv.org/abs/2010.16310
Publikováno v:
Inorganics, Vol 12, Iss 5, p 132 (2024)
The stepwise synthesis and characterization of three new mixed-ligand organometallic tetranuclear platinum squares were achieved. All of the complexes were constituted by the conjunction of two (2,2′-bpy)Pt-terph-Pt(2,2′-bpy) (terph = p-terphenyl
Externí odkaz:
https://doaj.org/article/7f3f7b0f00c046c886b9c24088955ffd
Autor:
Theodoros Tsolis, Dimitra Kyriakou, Evangelia Sifnaiou, Dimitrios Thomos, Dimitrios Glykos, Constantinos G. Tsiafoulis, Achilleas Garoufis
Publikováno v:
Molecules, Vol 29, Iss 5, p 1111 (2024)
Extra virgin olive oil (EVOO) is recognized for its numerous health benefits, attributed to its rich phenolic components. NMR has emerged as a prevalent technique for precisely identifying these compounds. Among Mediterranean countries, Greece stands
Externí odkaz:
https://doaj.org/article/15762597e1b1485a81c2264187f6eff7