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Image Categorization Using Deep Learning, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor) ; Rabiee, Hamid Reza (Co-Advisor)
Abstract
The representation of data influences the explanation factors of data variations. Thus,the success of learner algorithms depends on the data representation. Our main contribution in this thesis is learning of high level and abstract representation using deep structure. One of the fundamental examples of representation learning is the AutoEncoders. The auto-encoder is a rigid framework that doesn’t consider explanation factors in terms of statistical concepts. So, the auto-encoders can be re-interpreted by seeing the decoder as the statistical model of interest. The role of encoder is a mechanism for inference in the model described by the decoder. Our purpose is to design such model with...
Cataloging briefImage Categorization Using Deep Learning, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor) ; Rabiee, Hamid Reza (Co-Advisor)
Abstract
The representation of data influences the explanation factors of data variations. Thus,the success of learner algorithms depends on the data representation. Our main contribution in this thesis is learning of high level and abstract representation using deep structure. One of the fundamental examples of representation learning is the AutoEncoders. The auto-encoder is a rigid framework that doesn’t consider explanation factors in terms of statistical concepts. So, the auto-encoders can be re-interpreted by seeing the decoder as the statistical model of interest. The role of encoder is a mechanism for inference in the model described by the decoder. Our purpose is to design such model with...
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