Convolutional neural networks for self-driving CARS on GPU

B. V. Tiulkin, N. V. Kulabukhova

Research output

Abstract

Self-driving vehicles are considered to be safer than those driven by humans. Since they are always aware of what is happening around them and focuses on all the details. But to be really safe and respond to all the events happening around the drones need to process information and make decisions in the shortest possible time. The challenge is to teach how to drive a vehicle without human with the help of deep learning power using visual data from the cameras installed on the machine. The problem is to process the amount of data in the real time. Convolutional neural networks (CNNs) are used for training data And the idea of how to use CNNs on graphical processing units is described.

Original languageEnglish
Pages (from-to)611-614
Number of pages4
JournalCEUR Workshop Proceedings
Volume2267
Publication statusPublished - 1 Jan 2018
Event8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018 - Dubna
Duration: 10 Sep 201814 Sep 2018

Fingerprint

Neural networks
Cameras
Processing
Graphics processing unit
Drones
Deep learning

Scopus subject areas

  • Computer Science(all)

Cite this

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Convolutional neural networks for self-driving CARS on GPU. / Tiulkin, B. V.; Kulabukhova, N. V.

In: CEUR Workshop Proceedings, Vol. 2267, 01.01.2018, p. 611-614.

Research output

TY - JOUR

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AU - Tiulkin, B. V.

AU - Kulabukhova, N. V.

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Y1 - 2018/1/1

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