Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Kosmas Kritsis"'
Publikováno v:
IEEE Access, Vol 10, Pp 44982-45000 (2022)
Automatically synthesizing dance motion sequences is an increasingly popular research task in the broader field of human motion analysis. Recent approaches have mostly used recurrent neural networks (RNNs), which are known to suffer from prediction e
Externí odkaz:
https://doaj.org/article/d7aadff3fd4a4d9f8a0740d4cb450af2
Autor:
Kosmas Kritsis, Theatina Kylafi, Maximos Kaliakatsos-Papakostas, Aggelos Pikrakis, Vassilis Katsouros
Publikováno v:
Frontiers in Artificial Intelligence, Vol 3 (2021)
Jazz improvisation on a given lead sheet with chords is an interesting scenario for studying the behaviour of artificial agents when they collaborate with humans. Specifically in jazz improvisation, the role of the accompanist is crucial for reflecti
Externí odkaz:
https://doaj.org/article/d11f9f5fbb884e9a87d4eae9e2268e86
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
Publikováno v:
ICMI
Recent advances in deep learning have enabled the extraction of high-level skeletal features from raw images and video sequences, paving the way for new possibilities in a variety of artificial intelligence tasks, including automatically synthesized
Publikováno v:
ICFHR
In this paper, we explore deep learning architectures applied to the air-writing recognition problem where a person writes text freely in the three dimensional space. We focus on handwritten digits, namely from 0 to 9, which are structured as multidi
Autor:
Vasileios Sevetlidis, Chairi Kiourt, Vassilis Katsouros, Alexandra D. Solomou, Spyridoula Stamouli, George Pavlidis, Kosmas Kritsis, George Karetsos
Publikováno v:
Sustainability, Vol 13, Iss 11865, p 11865 (2021)
Sustainability
Volume 13
Issue 21
Sustainability
Volume 13
Issue 21
Plant identification from images has become a rapidly developing research field in com- puter vision and is particularly challenging due to the morphological complexity of plants. The availability of large databases of plant images, and the research
Deep Convolutional and LSTM Neural Network Architectures on Leap Motion Hand Tracking Data Sequences
Publikováno v:
EUSIPCO
This paper focuses on the hand gesture recognition problem, in which input is a multidimensional time series signal acquired from a Leap Motion Sensor and output is a predefined set of gestures. In the present work, we propose the adoption of Convolu
Autor:
Athanasia Zlatintsi, Petros Maragos, Vassilis Katsouros, Christos Garoufis, Panagiotis Paraskevas Filntisis, Kosmas Kritsis
Publikováno v:
EUSIPCO
This paper presents a finalized version of an environment intended for performance and gestural interaction with three-dimensional virtual musical instruments, developed as a part of a larger educational platform, the iMuSciCA workbench. The environm
Autor:
Georgios Z. Papadopoulos, Antoine Gallais, Periklis Chatzimisios, Kosmas Kritsis, Thomas Noel
Publikováno v:
IEEE Communications Magazine
IEEE Communications Magazine, Institute of Electrical and Electronics Engineers, 2016, 54 (1), pp.122-128. ⟨10.1109/MCOM.2016.7378437⟩
IEEE Communications Magazine, 2016, 54 (1), pp.122-128. ⟨10.1109/MCOM.2016.7378437⟩
IEEE Communications Magazine, Institute of Electrical and Electronics Engineers, 2016, 54 (1), pp.122-128. ⟨10.1109/MCOM.2016.7378437⟩
IEEE Communications Magazine, 2016, 54 (1), pp.122-128. ⟨10.1109/MCOM.2016.7378437⟩
Verification of theoretical analysis is a vital step in the development of an application or a protocol for wireless networks. Most proposals are evaluated through mathematical analysis followed by either simulation or experimental validation campaig
Autor:
Athanasia Zlatintsi, Panagiotis Paraskevas Filntisis, Vassilis Katsouros, Christos Garoufis, Petros Maragos, Aggelos Gkiokas, Maximos A. Kaliakatsos-Papakostas, Kosmas Kritsis, Antigoni Tsiami
Publikováno v:
Audio Mostly Conference
We present a web-based real-time application that enables gestural interaction with virtual instruments for musical expression. Skeletons of the users are tracked by a Kinect sensor, while the performance of the virtual instruments is accomplished us