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Full-Text Articles in Physical Sciences and Mathematics
Deep Parameter Selection For Classic Computer Vision Applications, Michael Whitney
Deep Parameter Selection For Classic Computer Vision Applications, Michael Whitney
Theses and Dissertations
A trend in computer vision today is to retire older, so-called "classic'' methods in favor of ones based on deep neural networks. This has led to tremendous improvements in many areas, but for some problems deep neural solutions may not yet exist or be of practical application. For this and other reasons, classic methods are still widely used in a variety of applications. This paper explores the possibility of using deep neural networks to improve these older methods instead of replace them. In particular, it addresses the issue of parameter selection in these algorithms by using a neural network to …
The "What"-"Where" Network: A Tool For One-Shot Image Recognition And Localization, Daniel Hurlburt
The "What"-"Where" Network: A Tool For One-Shot Image Recognition And Localization, Daniel Hurlburt
Theses and Dissertations
One common shortcoming of modern computer vision is the inability of most models to generalize to new classes—one/few shot image recognition. We propose a new problem formulation for this task and present a network architecture and training methodology to solve this task. Further, we provide insights into how careful focus on how not just the data, but the way data presented to the model can have significant impact on performance. Using these method, we achieve high accuracy in few-shot image recognition tasks.