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Transcript of Lightweight Road ManagerG1)%94 ?E+library.jsce.or.jp/jsce/open/00045/2016/41-0044.pdfsystem using a...

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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 ).

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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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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.

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