Convolutional neural networks for self-driving CARS on GPU

Standard

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: Contribution to journal › Conference article › peer-review

BibTeX

@article{a92eaa1e7acf4864a24ad3a834f34f7f,

title = "Convolutional neural networks for self-driving CARS on GPU",

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.",

keywords = "Convolutional neural networks, GPU, High-performance computing, Self-driving cars",

author = "Tiulkin, {B. V.} and Kulabukhova, {N. V.}",

year = "2018",

month = jan,

day = "1",

language = "English",

volume = "2267",

pages = "611--614",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "RWTH Aahen University",

note = "8th International Conference {"}Distributed Computing and Grid-Technologies in Science and Education{"}, GRID 2018 ; Conference date: 10-09-2018 Through 14-09-2018",

}

RIS

TY - JOUR

T1 - Convolutional neural networks for self-driving CARS on GPU

AU - Tiulkin, B. V.

AU - Kulabukhova, N. V.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

KW - Convolutional neural networks

KW - GPU

KW - High-performance computing

KW - Self-driving cars

UR - http://www.scopus.com/inward/record.url?scp=85060084972&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85060084972

VL - 2267

SP - 611

EP - 614

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018

Y2 - 10 September 2018 through 14 September 2018

ER -

ID: 38713921