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Loss-Augmented Structured Learning for Semantic Labeling

Rahmatollahi Namin, Shahin

Description

Semantic segmentation is among the most significant applications in computer vision. The goal of semantic segmentation is to understand a scene by learning to classify different regions of the scene to meaningful predefined classes. There are different schemes to perform this task such as probabilistic graphical models and deep learning. These methods are among the most successful approaches to address this task. The focus of researchers in the field of semantic segmentation is to propose...[Show more]

CollectionsOpen Access Theses
Date published: 2019
Type: Thesis (PhD)
URI: http://hdl.handle.net/1885/187631
DOI: 10.25911/5f58afd977273

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