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Feature Extraction and K-means Clustering Approach to Explore Important Features of Urban Identity

Submitting institution: The University of Kent
Unit of assessment: 13 - Architecture, Built Environment and Planning
Output identifier: 14578
Type: E - Conference contribution
DOI: 10.1109/ICMLA.2017.00015
Title of conference / published proceedings: 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)
First page: 1139
Volume: 0
Issue: 0
ISSN: 0000000
Open access status: Compliant
Month of publication: January
Year of publication: 2018
URL: https://kar.kent.ac.uk/68960/
Supplementary information: -
Request cross-referral to: -
Output has been delayed by COVID-19: No
COVID-19 affected output statement: -
Forensic science: No
Criminology: No
Interdisciplinary: No
Number of additional authors: 2
Research group(s): -
Proposed double-weighted: No
Reserve for an output with double weighting: Yes
Additional information: -
Author contribution statement: -
Non-English: No
English abstract: -