Lightweight Road ManagerG1)%94 ?E+library.jsce.or.jp/jsce/open/00045/2016/41-0044.pdfsystem using a...
Transcript of Lightweight Road ManagerG1)%94 ?E+library.jsce.or.jp/jsce/open/00045/2016/41-0044.pdfsystem using a...
Lightweight Road Manager
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Key Words: Smartphone application deep learning road damage status citizen data
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System Since Initiated by Area Chiba Report (Chiba-repo) August 2014 Public sector Chiba City
Cambridge iReport
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FixMyStreet February 2007 NPO UK Japan
NYC311 online March 2003 Public sector New York City
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λ e F3 () Vol.69 No.2 I_54-I_62 2013.
2) Offenhuber Dietmar. Infrastructure legibility a com-parative analysis of open311 based citizen feedback sys-tems Cambridge Journal of Regions, 2014.
3) King Stephen F. and Paul Brown Fix my street or else: using the internet to voice local public service con-cerns Proceedings of the 1st international conference on Theory and practice of electronic governance 2007.
4) 311 City Services the City of Chicago s Official Site <http://www.cityofchicago.org/city/en/depts/311/supp_info/311hist.html> ( 2016 6 30 ).
5) <http://chibarepo.force.com> ( 2016 6 30 ).
6) Youngtae Jo and Seungki Ryu Pothole detection system using a black-box camera Sensors 15.11 pp.29316-29331 2015.
7) Zou Qin et al. CrackTree: Automatic crack detec-tion from pavement images, Pattern Recognition Letters 33.3, pp.227-238, 2012.
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43. 7 pp.31-34 2008. 9)
te i
E1 ( ) Vol.70 No.3 I_1-I_8 2014. 10) Yu X. & Salari E. Pavement pothole detection
and severity measurement using laser imaging, Elec-tro/Information Technology (EIT), IEEE International Conference, pp.1-5, 2011.
11) Srinivas S. Sarvadevabhatla R. K. Mopuri K. R. Prabhu N. Kruthiventi S. S. & Babu R. V. A taxonomy of deep convolutional neural nets for computer vision, arXiv preprint arXiv:1601.06615, 2016.
12) Iandola F. N. Moskewicz M. W. Ashraf K. Han S. Dally W. J. & Keutzer K. SqueezeNet: AlexNet-level accuracy with 50x fewer pa-rameters and < 1MB model size, arXiv preprint arXiv:1602.0736, 2016.
13) Krizhevsky A. Sutskever I. & Hinton G. E.Imagenet classification with deep convolutional neural networks, Advances in Neural Information Processing Systems , pp.1097-1105, 2012.
14) Chatfield K Simonyan K Vedaldi A & Zisserman A. Return of the devil in the details: delv-ing deep into convolutional nets, 2014.
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