Abstract

aplicação de novas tecnologias tem afetado profundamente a indústria automobilística, especialmente quando se fala de carros autônomos. O cenário de auto-condução está próximo de se tornar realidade, entretanto, muitos desafios ainda precisam ser resolvidos. Outro aspecto [...]

Abstract

In the development of assistive robots, a major challenge is to improve the spatial perception of robots for object identification in various scenarios. For this purpose, it is necessary to develop tools for analysis and processing of artificial stereo vision data. For this reason, [...]

Abstract

International audience; Good, efficient and reliable public transportation systems are of crucial importance for all major cities today. In this paper, we propose a concrete solution to a particular problem: improve the prediction of the bus arrival time at each bus stop station on [...]

Abstract

The flexibility and cost efficiency of traffic monitoring using Unmanned Aerial Vehicles (UAVs) has made such a proposition an attractive topic of research. To date, the main focus was placed on the types of sensors used to capture the data, and the alternative data processing options [...]

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Neural networks (NNs) as an alternative method for universal approximation of differential equations have proven to be computationally efficient and still sufficiently accurate compared to established methods such as the finite volume method (FVM). Additionally, analysing weights [...]

Abstract

This paper analyzes the possibilities of using convolutional and recurrent neural networks to predict the indices of industrial production of the Russian economy. Since the indices are [...]

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The aim of this study is to develop new methods for forecasting time series with data of different frequencies among exogenous factors; forecasting the indicators of the wholesale electricity market in Russia using methods of combining data of different frequencies, including those [...]