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Deep learning and DCT-based hand-crafted features for computer vision tasks
(University of Missouri--Columbia, 2022)
Feature extraction and matching are critical components for many computer vision tasks including camera pose estimation, 3D reconstruction, simultaneous localization and mapping (SLAM), and object tracking, etc. Features ...
Single and multi-object video tracking using local and deep architectures
(University of Missouri--Columbia, 2022)
Moving object tracking is a fundamental computer vision task with a wide variety of real-life applications ranging from surveillance and autonomous systems to biomedical video analysis. A robust, accurate, scalable, and ...
Deep learning architectures for 2D and 3D scene perception
(University of Missouri--Columbia, 2021)
Scene understanding is a fundamental problem in computer vision tasks, that is being more intensively explored in recent years with the development of deep learning. In this dissertation, we proposed deep learning structures ...