1 research outputs found
Deep learning for visual understanding
With the dramatic growth of
the image data on the web, there is an increasing demand of the algorithms
capable of understanding the visual information automatically. Deep learning,
served as one of the most significant breakthroughs, has brought revolutionary
success in diverse visual applications, including image classification, object
detection, image segmentation, image captioning and etc. The purpose of this
thesis is to explore and design new deep learning algorithms for better visual
understanding. The main purpose of the thesis is to develop new algorithms
which can improve the understanding of images. To fulfill this, it focuses on
two visual applications: image classification and image captioning. Image
classification aims to classify images into pre-defined categories, and helps
people to know what objects the images contain. Image captioning attempts to
generate a sentence to describe the images. In addition to the object, the
generated sentence should also contain the action, relation and etc. China Scholarship CouncilComputer Systems, Imagery and Medi