Akıllı araç görüşünde derin evrişimli sinir ağı kullanılarak şerit segmentasyonu ve yol tespiti
2024
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Advisor: Dr. Öğr. Üyesi Timur İnan
Abstract (EN)
This thesis will delve into the intricacies of designing, training, and evaluating a deep CNN architecture for lane segmentation and subsequently harness the discriminative power of SVMs for road detection. Through a comprehensive investigation of these methodologies, this thesis aims to contribute to the advancement of smart car vision systems, ultimately paving the way for safer and more reliable autonomous driving solutions in an ever-evolving urban landscape. As society becomes increasingly reliant on digital communication and data, the ability to understand, process, and generate human language has become a critical component in various applications, from virtual assistants and sentiment analysis to machine translation and content recommendation systems.
Author
Sarah Kadhım Hwaıdı Al Fadhlı
How to Cite
Sarah Kadhım Hwaıdı Al Fadhlı (Master Thesis). Akıllı araç görüşünde derin evrişimli sinir ağı kullanılarak şerit segmentasyonu ve yol tespiti, 2024, Altınbaş University.
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