Deep Active Learning for Civil Infrastructure Defect Detection and Classification-Reference-Cited by-同舟云学术

Deep Active Learning for Civil Infrastructure Defect Detection and Classification

Published:2017-06-13 Issue: Volume: Page:
ISSN:
Container-title:Computing in Civil Engineering 2017
language:
Short-container-title:

Author:

Feng Chen¹¹²¹,Liu Ming-Yu¹¹²¹,Kao Chieh-Chi¹¹²¹,Lee Teng-Yok¹¹²¹

Affiliation:

1. Mitsubishi Electric Research Laboratories (MERL), 201 Broadway, Cambridge, MA 02139.

2. Univ. of California, Santa Barbara.

Publisher

American Society of Civil Engineers

Link

http://ascelibrary.org/doi/pdf/10.1061/9780784480823.036

Reference19 articles.

1. ASCE. (2013). "2013 Report Card for America's Infrastructure." Reston VA: American Society of Civil Engineers. Retrieved from http://ascelibrary.org/doi/abs/10.1061/9780784478837

2. Cement P. (2001). "Concrete slab surface defects: Causes prevention repair." Portland Cement Association.

3. Dai J. He K. and Sun J. (2016 June). "Instance-Aware Semantic Segmentation via Multi-Task Network Cascades." The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

4. Freytag A. Rodner E. and Denzler J. (2014). "Selecting influential examples: Active learning with expected model output changes." European Conference on Computer Vision 562-- 577.

5. He K. Zhang X. Ren S. and Sun J. (2015). "Deep Residual Learning for Image Recognition." arXiv prepring arXiv:1506.01497.

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