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Smart city and geospatiality: Hobart deeply learned

conference contribution
posted on 2023-05-23, 09:44 authored by Jagannath Aryal, Dutta, R
We propose a cloud computing based big data framework using Deep Neural Networks, to learn urban objects from very high-resolution image in an abstract optimized manner. Automatic recognition of such objects would be essential to minimize big data accessibility issues and increase efficiency of urban dynamics monitoring and planning. We have shown that deep learning could be a way forward towards that complex aim with very high accuracy rates.

History

Publication title

Proceedings of the 2015 IEEE 31st International Conference on Data Engineering Workshops

Pagination

108-109

ISBN

978-1-4799-8441-1

Department/School

School of Geography, Planning and Spatial Sciences

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

United States of America

Event title

2015 IEEE 31st International Conference on Data Engineering Workshops

Event Venue

Seoul, South Korea

Date of Event (Start Date)

2015-04-13

Date of Event (End Date)

2015-04-17

Rights statement

Copyright 2015 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in the earth sciences

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    University Of Tasmania

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