Deep Learning in Autonomous Driving
| dc.contributor.advisor | Adamkó, Attila | |
| dc.contributor.author | Eltaweel, Abdulrahman Mohamed Ramadan Ibrahim | |
| dc.contributor.department | DE--Informatikai Kar | hu_HU |
| dc.date.accessioned | 2021-12-02T13:24:58Z | |
| dc.date.available | 2021-12-02T13:24:58Z | |
| dc.date.created | 2021-12-01 | |
| dc.description.abstract | Where deep learning in autonomous driving was and is still evolving in the future, and how its applications affect our lives. Deep Learning and Artificial Intelligence (AI) will define the mobility of the future in both personal and corporate applications. AI is the most potent technological force of our time. In this thesis, I have addressed several areas of deep learning, especially autonomous driving utilizing convolutional neural networks (CNNs). Using CNN in the simulator to create self-driving automobiles that do not require human intervention. demonstrating the significance and enormous influence that autonomy might have. From reducing accidents to saving money, increasing productivity, and other environmental advantages. | hu_HU |
| dc.description.course | Business Informatics | hu_HU |
| dc.description.degree | BSc/BA | hu_HU |
| dc.format.extent | 52 | hu_HU |
| dc.identifier.uri | http://hdl.handle.net/2437/326020 | |
| dc.language.iso | en | hu_HU |
| dc.subject | Autonomous driving | hu_HU |
| dc.subject | Artificial intelligence | hu_HU |
| dc.subject | Self-driving | hu_HU |
| dc.subject | convolutional neural networks | hu_HU |
| dc.subject | End to End Learning for Self-Driving Cars | hu_HU |
| dc.subject.dspace | DEENK Témalista::Informatika | hu_HU |
| dc.title | Deep Learning in Autonomous Driving | hu_HU |