Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Harar, Pavol"'
In cryo-electron microscopy, accurate particle localization and classification are imperative. Recent deep learning solutions, though successful, require extensive training data sets. The protracted generation time of physics-based models, often empl
Externí odkaz:
http://arxiv.org/abs/2304.02011
We present an algorithm and package, Redistributor, which forces a collection of scalar samples to follow a desired distribution. When given independent and identically distributed samples of some random variable $S$ and the continuous cumulative dis
Externí odkaz:
http://arxiv.org/abs/2210.14219
Autor:
Kovac, Daniel, Mekyska, Jiri, Aharonson, Vered, Harar, Pavol, Galaz, Zoltan, Rapcsak, Steven, Orozco-Arroyave, Juan Rafael, Brabenec, Lubos, Rektorova, Irena
Publikováno v:
In Biomedical Signal Processing and Control February 2024 88 Part B
Autor:
Harar, Pavol, Galaz, Zoltan, Alonso-Hernandez, Jesus B., Mekyska, Jiri, Burget, Radim, Smekal, Zdenek
Publikováno v:
Neural Computing and Applications (2018): 1-11
Automatic objective non-invasive detection of pathological voice based on computerized analysis of acoustic signals can play an important role in early diagnosis, progression tracking and even effective treatment of pathological voices. In search tow
Externí odkaz:
http://arxiv.org/abs/1907.06129
Autor:
Harar, Pavol, Alonso-Hernandez, Jesus B., Mekyska, Jiri, Galaz, Zoltan, Burget, Radim, Smekal, Zdenek
Publikováno v:
In 2017 international conference and workshop on bioinspired intelligence (IWOBI), pp. 1-4. IEEE, 2017
This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN). We used voice recordings of sustained vowel /a/ produced at normal pitch from German corpus Saarbruecken Voice Database (SVD). This corpus
Externí odkaz:
http://arxiv.org/abs/1907.05905
Convolutional neural network (CNN) architectures have originated and revolutionized machine learning for images. In order to take advantage of CNNs in predictive modeling with audio data, standard FFT-based signal processing methods are often applied
Externí odkaz:
http://arxiv.org/abs/1903.08950
Autor:
Breger, Anna, Orlando, Jose Ignacio, Harar, Pavol, Dörfler, Monika, Klimscha, Sophie, Grechenig, Christoph, Gerendas, Bianca S., Schmidt-Erfurth, Ursula, Ehler, Martin
Publikováno v:
Journal of Mathematical Imaging and Vision, 2019
The use of orthogonal projections on high-dimensional input and target data in learning frameworks is studied. First, we investigate the relations between two standard objectives in dimension reduction, preservation of variance and of pairwise relati
Externí odkaz:
http://arxiv.org/abs/1901.07598
Publikováno v:
Axioms 2019, 8(4), 106
This paper introduces Gabor scattering, a feature extractor based on Gabor frames and Mallat's scattering transform. By using a simple signal model for audio signals specific properties of Gabor scattering are studied. It is shown that for each layer
Externí odkaz:
http://arxiv.org/abs/1706.08818
Autor:
Harar, Pavol1 (AUTHOR) pavol.harar@vut.cz, Galaz, Zoltan1 (AUTHOR), Alonso-Hernandez, Jesus B.2 (AUTHOR), Mekyska, Jiri1 (AUTHOR), Burget, Radim1 (AUTHOR), Smekal, Zdenek1 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Oct2020, Vol. 32 Issue 20, p15747-15757. 11p.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.