Zobrazeno 1 - 10
of 275
pro vyhledávání: '"Krylov Vladimír"'
We propose a pipeline for combined multi-class object geolocation and height estimation from street level RGB imagery, which is considered as a single available input data modality. Our solution is formulated via Markov Random Field optimization with
Externí odkaz:
http://arxiv.org/abs/2305.08232
Publikováno v:
IMVIP 2018
In this paper we propose an approach to perform semantic segmentation of 3D point cloud data by importing the geographic information from a 2D GIS layer (OpenStreetMap). The proposed automatic procedure identifies meaningful units such as buildings a
Externí odkaz:
http://arxiv.org/abs/2108.06306
We show how parameter redundancy in Convolutional Neural Network (CNN) filters can be effectively reduced by pruning in spectral domain. Specifically, the representation extracted via Discrete Cosine Transform (DCT) is more conducive for pruning than
Externí odkaz:
http://arxiv.org/abs/2010.12110
Convolutional neural networks (CNNs) learn filters in order to capture local correlation patterns in feature space. We propose to learn these filters as combinations of preset spectral filters defined by the Discrete Cosine Transform (DCT). Our propo
Externí odkaz:
http://arxiv.org/abs/2001.06570
Akademický článek
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Publikováno v:
European Signal Processing Conference (EUSIPCO) 2019
Convolutional neural networks (CNNs) are very popular nowadays for image processing. CNNs allow one to learn optimal filters in a (mostly) supervised machine learning context. However this typically requires abundant labelled training data to estimat
Externí odkaz:
http://arxiv.org/abs/1905.00135
Autor:
Grin, Andrey, Lvov, Ivan, Talypov, Aleksandr, Kordonskiy, Anton, Khushnazarov, Ulugbek, Krylov, Vladimir
Publikováno v:
In Neurocirugía March-April 2023 34(2):80-86
Akademický článek
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Convolutional neural networks (CNNs) learn filters in order to capture local correlation patterns in feature space. In contrast, in this paper we propose harmonic blocks that produce features by learning optimal combinations of spectral filters defin
Externí odkaz:
http://arxiv.org/abs/1812.03205
Autor:
Lvov, Ivan, Grin, Andrey, Talypov, Aleksandr, Smirnov, Vladimir, Kordonskiy, Anton, Barbakadze, Zaali, Abdrafiev, Rinat, Krylov, Vladimir
Publikováno v:
In World Neurosurgery November 2022 167:e1169-e1184