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Full-Text Articles in Physical Sciences and Mathematics
Dataset And Evaluation Of Self-Supervised Learning For Panoramic Depth Estimation, Ryan Nett
Dataset And Evaluation Of Self-Supervised Learning For Panoramic Depth Estimation, Ryan Nett
Master's Theses
Depth detection is a very common computer vision problem. It shows up primarily in robotics, automation, or 3D visualization domains, as it is essential for converting images to point clouds. One of the poster child applications is self driving cars. Currently, the best methods for depth detection are either very expensive, like LIDAR, or require precise calibration, like stereo cameras. These costs have given rise to attempts to detect depth from a monocular camera (a single camera). While this is possible, it is harder than LIDAR or stereo methods since depth can't be measured from monocular images, it has to …
Leveraging Defects Life-Cycle For Labeling Defective Classes, Bailey R. Vandehei
Leveraging Defects Life-Cycle For Labeling Defective Classes, Bailey R. Vandehei
Master's Theses
Data from software repositories are a very useful asset to building dierent kinds of
models and recommender systems aimed to support software developers. Specically,
the identication of likely defect-prone les (i.e., classes in Object-Oriented systems)
helps in prioritizing, testing, and analysis activities. This work focuses on automated
methods for labeling a class in a version as defective or not. The most used methods
for automated class labeling belong to the SZZ family and fail in various circum-
stances. Thus, recent studies suggest the use of aect version (AV) as provided by
developers and available in the issue tracker such as …