Deep learning with constrained data resource

This report provides a solution to solve the few samples learning (FSL) problems. The method can achieve a better accuracy compared to simple full-supervised learning methods, especially the problem becomes to a one-shotting problem.

Saved in:

Bibliographic Details
Main Author:	Mao, Jiangtian
Other Authors:	Xie Lihua
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2022
Subjects:	Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/158293
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-158293
record_format	dspace
spelling	sg-ntu-dr.10356-1582932023-07-07T18:55:23Z Deep learning with constrained data resource Mao, Jiangtian Xie Lihua School of Electrical and Electronic Engineering ELHXIE@ntu.edu.sg Engineering::Electrical and electronic engineering This report provides a solution to solve the few samples learning (FSL) problems. The method can achieve a better accuracy compared to simple full-supervised learning methods, especially the problem becomes to a one-shotting problem. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-31T07:55:20Z 2022-05-31T07:55:20Z 2022 Final Year Project (FYP) Mao, J. (2022). Deep learning with constrained data resource. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158293 https://hdl.handle.net/10356/158293 en application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering
spellingShingle	Engineering::Electrical and electronic engineering Mao, Jiangtian Deep learning with constrained data resource
description	This report provides a solution to solve the few samples learning (FSL) problems. The method can achieve a better accuracy compared to simple full-supervised learning methods, especially the problem becomes to a one-shotting problem.
author2	Xie Lihua
author_facet	Xie Lihua Mao, Jiangtian
format	Final Year Project
author	Mao, Jiangtian
author_sort	Mao, Jiangtian
title	Deep learning with constrained data resource
title_short	Deep learning with constrained data resource
title_full	Deep learning with constrained data resource
title_fullStr	Deep learning with constrained data resource
title_full_unstemmed	Deep learning with constrained data resource
title_sort	deep learning with constrained data resource
publisher	Nanyang Technological University
publishDate	2022
url	https://hdl.handle.net/10356/158293
_version_	1772828531928072192

Deep learning with constrained data resource

Similar Items