Effect of the Learning Image Combinations and Weather Parameters in the PM Estimation from CCTV Images
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Won, Taeyeon
(Dept. of Advanced Technology Fusion, Konkuk University)
Eo, Yang Dam (Dept. of Civil and Environmental Engineering, Konkuk University) Sung, Hong ki (Dept. of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology) Chong, Kyu soo (Dept. of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology) Youn, Junhee (Dept. of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology) |
1 | Awad, M. and Khanna, R. (2015), Support Vector Regression, Efficient Learning Machines, pp. 67-80. |
2 | Behnke, S. (2003), Hierarchical Neural Networks for Image Interpretation, Lecture Notes in Computer Science, Draft submitted to Springer-Verlag. Vol. 2766 |
3 | Bo, Q., Yang, W., Rijal, N., Xie, Y., Feng, U., and Zhang, J. (2018), Particle Pollution Estimation from Images Using Convolutional Neural Network and Weather Features, IEEE International Conference on Image Processing (ICIP), Athens, pp.3433-3437 |
4 | Chao, Z., Yan, J., Li, C., Rui, X., Liu, L., and Bie, R. (2017), Image-based air quality analysis using deep convolutional neural network, MM '16: Proceedings of the 24th ACM international conference on Multimedia, pp. 297-301. |
5 | Cortes, C. and Vapnik, V. (1995), Support-vector networks, Machine learning, 20, no.3, 273-297. DOI |
6 | Harrison, R.M., Deacon, A.R., Jones, M.R., and Appleby, R.S. (1997), Sources and processes affecting concentrations of PM10 and PM2.5 particulate matter in Birmingham (U.K.), Atmospheric Environment, Volume 31, Issues 24, December, pp. 4103-4117. DOI |
7 | LeCun, Y., Boser, B., Denker, J.S., Henderson, D., Howard, R.E., Hubbard, and W., Jackel, L.D., (1989), Backpropagation Applied to Handwritten Zip Code Recognition, Neural Computation, Volume 1, Issue 4, Dec., pp. 541 - 551. DOI |
8 | LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998), Gradient-based learning applied to document recognition. Proceedings of the IEEE, Vol. 86, No.11, pp. 2278-2324. DOI |
9 | Li, Y., Huang, J., and Luo, J. (2015), Using user generated online photos to estimate and monitor air pollution in major cities, Computer Vision and Pattern Recognition, arXi, https://arxiv.org/abs/1508.05028 |
10 | Liu, Ch., Tsow, F., Zou, Y., and Tao, N. (2016), Particle pollution estimation based on image analysis, PloS one, 11, no.2 |
11 | Lou, C., Liu, H., Li, Y., Peng, Y., Wang, J., and Dai, L. (2017), Relationships of relative humidity with PM 2.5 and PM 10 in the Yangtze River Delta, China, Environ Monit Assess, 2017 Oct 23;189(11):582, doi:10.1007/s10661-017-6281-z DOI |
12 | Mao, J., Phommasak, U., Watanabe, S. and Shioya, H. (2014), Detecting foggy images and estimating the haze degree factor, Journal of Computer Science & Systems Biology, 7:6 |
13 | Chakma, A., Vizena, B., Cao, T., Lin, J., and Zhang, J. (2017), On Estimating Air Pollution from Photos Using Convolutional Neural Network, IEEE International Conference on Image Processing (ICIP), pp.3949-3952, doi: 10.1109/ICIP.2017.8297023. |
14 | Pope III, C.A., Ezzati, M., and Dockery D.W. (2009) Fine-Particulate Air Pollution and Life Expectancy in the United States, N Engl J Med, Volume 360, pp. 376-386. DOI |
15 | Pope III, C.A. and Dockery D.W. (2012) Health Effects of Fine Particulate Air Pollution: Lines that Connect, Journal of the air & waste management association, Volume 56, Issues 6, pp. 709-742. DOI |
16 | Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., and Fei, L.F. (2014), ImageNet Large Scale Visual Recognition Challenge, International Journal of Computer Vision, Vol. 115, Issue. 3, pp. 211-252. DOI |
17 | Simonyan, K., and Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition, arXiv, https://arxiv.org/abs/1409.1556 |
18 | Song, A.R., and Kim, Y.I. (2017), Deep Learning-based Hyperspectral Image Classification with Application to Environmental Geographic Information Systems, Korean Journal of Remote Sensing, v. 33 no. 6 pt. 2, pp. 1061-1073. (in Korean with English abstract) |
19 | Tai, A.P.K., Mickley, L.J., and Jacob, D.J. (2010), Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change, Atmospheric Environment, 44, 32, pp. 3976-3984. DOI |
20 | Zhao, H., Zhang, W., Sun, H., and Xue, B. (2019), Embedded Deep Learning for Ship Detection and Recognition, Future Internet, 11(2), 53 DOI |
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