Lalwani, Kapil Kishor (2023) Intelligent Transportation System for Lane Detection using Focus-based Instance Segmentation. Masters thesis, Dublin, National College of Ireland.
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Abstract
Lane detection is an essential feature for developing intelligent transportation systems that can prevent road accidents due to undetected lane changes. The study will propose a method for reducing road accidents by using computer vision robotics to detect lanes for self-driving cars. The comprehensive aim of the research is to determine one such intelligent transportation system that can use focus-based instance segmentation for detecting lanes and improving autonomous vehicle transportation. This research proposes a technique for detecting traffic lanes using focus-based instance segmentation for vehicle detection on the road and highlighting lanes with drivable space. The proposed network uses a loss-trained hourglass model. Additionally, this model is trained multiple times using the same loss function to achieve competitive accuracy and a high proportion of false-positive results. The information comes from the German Traffic Sign Detection Benchmark (GTSDB), which is public data.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Basilio, Jorge UNSPECIFIED |
Uncontrolled Keywords: | fast region-based convolutional neural network; focus-based image segmentation; hough transform; hourglass model |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TE Highway engineering. Roads and pavements Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence |
Divisions: | School of Computing > Master of Science in Data Analytics |
Depositing User: | Tamara Malone |
Date Deposited: | 19 May 2023 15:43 |
Last Modified: | 19 May 2023 15:43 |
URI: | https://norma.ncirl.ie/id/eprint/6608 |
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