The understanding of the environment is the critical ability not only for the living creature but also for automation fields like the robot, automated car, and intelligent system. Especially for some essential task in the domain of automotive such as autonomous driving, path planning, localization, and object detection, the more information we gather, the better the result we get. Intelligent vehicle technology relies on sensorial perception to understand the surroundings of the vehicle. The objective of the research is developing a cooperative online perception system with semantic segmentation for automated driving and improving the current semantic segmentation framework to make it more robust and more suitable for our future projects.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:73111 |
| Date | 09 December 2020 |
| Creators | Ngo, Quang Thanh |
| Contributors | Hardt, Wolfram, Lindner, Philipp |
| Publisher | Technische Universität Chemnitz |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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