GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION

10.1109/ICME.2017.8019376

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Bibliographic Details
Main Authors:	Yin, Yifang, Liu, Zhenguang, Zimmermann, Roger
Other Authors:	CHEMICAL & BIOMOLECULAR ENGINEERING
Format:	Conference or Workshop Item
Published:	IEEE 2021
Subjects:	Science & Technology Technology Computer Science, Software Engineering Computer Science, Theory & Methods Engineering, Electrical & Electronic Computer Science Engineering
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/200729
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-200729
record_format	dspace
spelling	sg-nus-scholar.10635-2007292024-11-10T04:57:07Z GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION Yin, Yifang Liu, Zhenguang Zimmermann, Roger CHEMICAL & BIOMOLECULAR ENGINEERING Dr Yifang Yin Science & Technology Technology Computer Science, Software Engineering Computer Science, Theory & Methods Engineering, Electrical & Electronic Computer Science Engineering 10.1109/ICME.2017.8019376 IEEE International Conference on Multimedia and Expo (ICME) 1015-1020 2021-09-20T07:50:04Z 2021-09-20T07:50:04Z 2017-01-01 2021-09-19T15:43:14Z Conference Paper Yin, Yifang, Liu, Zhenguang, Zimmermann, Roger (2017-01-01). GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION. IEEE International Conference on Multimedia and Expo (ICME) : 1015-1020. ScholarBank@NUS Repository. https://doi.org/10.1109/ICME.2017.8019376 9781509060672 19457871 1945788X https://scholarbank.nus.edu.sg/handle/10635/200729 IEEE Elements
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Science & Technology Technology Computer Science, Software Engineering Computer Science, Theory & Methods Engineering, Electrical & Electronic Computer Science Engineering
spellingShingle	Science & Technology Technology Computer Science, Software Engineering Computer Science, Theory & Methods Engineering, Electrical & Electronic Computer Science Engineering Yin, Yifang Liu, Zhenguang Zimmermann, Roger GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION
description	10.1109/ICME.2017.8019376
author2	CHEMICAL & BIOMOLECULAR ENGINEERING
author_facet	CHEMICAL & BIOMOLECULAR ENGINEERING Yin, Yifang Liu, Zhenguang Zimmermann, Roger
format	Conference or Workshop Item
author	Yin, Yifang Liu, Zhenguang Zimmermann, Roger
author_sort	Yin, Yifang
title	GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION
title_short	GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION
title_full	GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION
title_fullStr	GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION
title_full_unstemmed	GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION
title_sort	geographic information use in weakly-supervised deep learning for landmark recognition
publisher	IEEE
publishDate	2021
url	https://scholarbank.nus.edu.sg/handle/10635/200729
_version_	1821203868905635840

GEOGRAPHIC INFORMATION USE IN WEAKLY-SUPERVISED DEEP LEARNING FOR LANDMARK RECOGNITION

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