Building Constraints, Geometric Invariants and Interpretability in Deep Learning: Applications in Computational Imaging and Vision

Building Constraints, Geometric Invariants and Interpretability in Deep Learning: Applications in Computational Imaging and Vision

abstract: Over the last decade, deep neural networks also known as deep learning, combined with large databases and specialized hardware for computation, have made major strides in important areas such as computer vision, computational imaging and natural language processing. However, such framework...

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Bibliographic Details
Other Authors: Lohit, Suhas Anand (Author)
Format: Doctoral Thesis
Language:English
Published: 2019
Subjects:
Electrical engineering
Computer science
Compressive sensing
Computer vision
Deep learning
Differential geometry
Machine learning
Signal processing
Online Access:http://hdl.handle.net/2286/R.I.55542

Internet

http://hdl.handle.net/2286/R.I.55542

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