Computer vision for driver assistance systems
الملخص
The objective of the proposed thesis is to illustrate the training, validation and evaluation of vehicle detection algorithms using computer vision and deep learning methods, and vehicle tracking in video sequences. Object detection poses a major challenge in localizing the object and finding its exact coordinates, in addition to determining its presence in the image. Objects in varying scales must also be detected in the image, and the algorithm chosen for object detection must be feasible for real-time detection. The research work focuses on a traditional machine learning approach and a deep learning approach for overcoming the object detection challenges, and object tracking algorithms, to improve the accuracy of object detection.
الكلمات المفتاحية
غير متوفر
التخصصات
رسائل وأطاريح مشابهة
- Advancing heat stress detection in dairy cows through machine learning and computer vision Shu, Hang · University of Liège · 2024
- Automated Activity Discovery and Object Detection With Computer Vision: Towards Unsupervised Learning for Breakfast to Surgery Michael Zhang · Harvard University · 2020
- Deep Zero- and Few-shot Learning in Computer Vision Hongguang Zhang · Australian National University · 2020
- Computer vision as a tool for forestry Filip Bång · KTH Royal Institute of Technology · 2019
- Distributed Intelligence for 3D Object Tracking in Autonomous Vehicles, A Multi-Sensor Approach to Object Tracking and Planning for Self-Driving Cars, Real-Time 3D Perception and Path Planning in Autonomous Systems,,Vision-Based Localization and Distributed Architecture for Driverless Cars,A Hybrid Deep Learning Framework for Object Detection and Trajectory Planning in Autonomous Vehicles Manas Madine · University of Massachusetts Amherst · 2023
- Deep learning with synthetic, temporal, and adversarial supervision Ankush Gupta · University of Oxford · 2018
