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Full-Text Articles in Physical Sciences and Mathematics
The Performance Of Random Prototypes In Hierarchical Models Of Vision, Kendall Lee Stewart
The Performance Of Random Prototypes In Hierarchical Models Of Vision, Kendall Lee Stewart
Dissertations and Theses
I investigate properties of HMAX, a computational model of hierarchical processing in the primate visual cortex. High-level cortical neurons have been shown to respond highly to particular natural shapes, such as faces. HMAX models this property with a dictionary of natural shapes, called prototypes, that respond to the presence of those shapes. The resulting set of similarity measurements is an effective descriptor for classifying images. Curiously, prior work has shown that replacing the dictionary of natural shapes with entirely random prototypes has little impact on classification performance. This work explores that phenomenon by studying the performance of random prototypes on …
Leveraging Contextual Relationships Between Objects For Localization, Clinton Leif Olson
Leveraging Contextual Relationships Between Objects For Localization, Clinton Leif Olson
Dissertations and Theses
Object localization is currently an active area of research in computer vision. The object localization task is to identify all locations of an object class within an image by drawing a bounding box around objects that are instances of that class. Object locations are typically found by computing a classification score over a small window at multiple locations in the image, based on some chosen criteria, and choosing the highest scoring windows as the object bounding-boxes. Localization methods vary widely, but there is a growing trend towards methods that are able to make localization more accurate and efficient through the …