Uncertainty quantification using bayesian neural networks: application to plant disease detection and physics guided machine learning

dc.contributor.advisor	Bhatia, Udit
dc.contributor.author	Vagadiya, Jenilkumar Virendra
dc.date.accessioned	2021-10-27T14:12:41Z
dc.date.available	2021-10-27T14:12:41Z
dc.date.issued	2021
dc.identifier.citation	Vagadiya, Jenilkumar Virendra (2021). Uncertainty quantification using bayesian neural networks: application to plant disease detection and physics guided machine learning. Gandhinagar: Indian Institute of Technology Gandhinagar, 42p. (Acc. No.: T00844).
dc.identifier.uri	https://repository.iitgn.ac.in/handle/123456789/7135
dc.description.statementofresponsibility	by Jenilkumar Virendra Vagadiya
dc.format.extent	xii, 42p.: ill.; hbk.; 30cm.
dc.language.iso	en_US
dc.publisher	Indian Institute of Technology Gandhinagar
dc.subject	19210053
dc.subject	Physics Informed Machine Learning -- PIML
dc.subject	Support Vector Machine
dc.subject	Gaussian Process Regression
dc.subject	Variational Inference
dc.subject	Data collection And Augmentation
dc.title	Uncertainty quantification using bayesian neural networks: application to plant disease detection and physics guided machine learning
dc.type	Thesis
dc.contributor.department	Computer Science and Engineering
dc.description.degree	M.Tech