Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Papaioannou, Charilaos"'
We introduce Label-Combination Prototypical Networks (LC-Protonets) to address the problem of multi-label few-shot classification, where a model must generalize to new classes based on only a few available examples. Extending Prototypical Networks, L
Externí odkaz:
http://arxiv.org/abs/2409.11264
Autor:
Charalampopoulos, Andreas, Chatzis, Nikolas, Ntoulas-Panagiotopoulos, Foivos, Papaioannou, Charilaos, Potamianos, Alexandros
Fast feedforward networks (FFFs) are a class of neural networks that exploit the observation that different regions of the input space activate distinct subsets of neurons in wide networks. FFFs partition the input space into separate sections using
Externí odkaz:
http://arxiv.org/abs/2405.16836
Recent developments in MIR have led to several benchmark deep learning models whose embeddings can be used for a variety of downstream tasks. At the same time, the vast majority of these models have been trained on Western pop/rock music and related
Externí odkaz:
http://arxiv.org/abs/2307.09795
In this paper, we study the problem of producing a comprehensive video summary following an unsupervised approach that relies on adversarial learning. We build on a popular method where a Generative Adversarial Network (GAN) is trained to create repr
Externí odkaz:
http://arxiv.org/abs/2307.08145
Autor:
Papaioannou, Charilaos, Valiantzas, Ioannis, Giannakopoulos, Theodoros, Kaliakatsos-Papakostas, Maximos, Potamianos, Alexandros
Studying under-represented music traditions under the MIR scope is crucial, not only for developing novel analysis tools, but also for unveiling musical functions that might prove useful in studying world musics. This paper presents a dataset for Gre
Externí odkaz:
http://arxiv.org/abs/2211.11479
Publikováno v:
Acta Haematologica; 1979, Vol. 62 Issue 2, p78-80, 3p
