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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, RWe 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 WorkshopsPagination
108-109ISBN
978-1-4799-8441-1Department/School
School of Geography, Planning and Spatial SciencesPublisher
Institute of Electrical and Electronics EngineersPlace of publication
United States of AmericaEvent title
2015 IEEE 31st International Conference on Data Engineering WorkshopsEvent Venue
Seoul, South KoreaDate of Event (Start Date)
2015-04-13Date of Event (End Date)
2015-04-17Rights statement
Copyright 2015 IEEERepository Status
- Restricted