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Ensemble Learning on Deep Neural Networks for Image Caption Generation


Abstract Capturing the information in an image into a natural language sentence is

considered a difficult problem to be solved by computers. Image captioning involves not just detecting objects from images but understanding the interactions between the objects to be translated into relevant captions. So, expertise in the fields of computer vision paired with natural language processing are supposed to be crucial for this purpose. The sequence to sequence modelling strategy of deep neural networks is the traditional approach to generate a sequential list of words which are combined to represent the image. But these models suffer from the problem of high variance by not being able to generalize well on the training data.

The main focus of this thesi... (more)
Created Date 2019
Contributor Katpally, Harshitha (Author) / Bansal, Ajay (Advisor) / Acuna, Ruben (Committee member) / Gonzalez-Sanchez, Javier (Committee member) / Arizona State University (Publisher)
Subject Computer science
Type Masters Thesis
Extent 131 pages
Language English
Copyright
Note Masters Thesis Software Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis