Research output: Contribution to journal › Conference article › peer-review
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 language | English |
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Pages (from-to) | 611-614 |
Number of pages | 4 |
Journal | CEUR Workshop Proceedings |
Volume | 2267 |
State | Published - 1 Jan 2018 |
Event | 8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018 - Dubna, Russian Federation Duration: 10 Sep 2018 → 14 Sep 2018 |
ID: 38713921