Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159406
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dc.contributor.authorWang, Dongyingen_US
dc.date.accessioned2022-06-16T04:39:50Z-
dc.date.available2022-06-16T04:39:50Z-
dc.date.issued2022-
dc.identifier.citationWang, D. (2022). Scene understanding for autonomous vehicles with deep learning. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159406en_US
dc.identifier.urihttps://hdl.handle.net/10356/159406-
dc.description.abstractThis project aimed to carry out algorithm which is able to generate semantic images and then fuse the semantic images with point cloud to obtain point cloud with semantic information for the scene understanding tasks. This project can be seen as a base for scene understanding task, which covers a wide range of data designing and processing work. First of all, labeling strategies designed for semantic segmentation aimed to help with scene understanding tasks have been carried out. In addition, for semantic information generation, a semantic segmentation network integrating attention mechanism and all MLP layers upsampling technique was applied. Finally, to get abundant information, the semantic images are fused with the point cloud using an algorithm based on robotics geometric projection theories.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleScene understanding for autonomous vehicles with deep learningen_US
dc.typeThesis-Master by Courseworken_US
dc.contributor.supervisorWang Dan Weien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
dc.contributor.supervisoremailEDWWANG@ntu.edu.sgen_US
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