1 |
Lei, Y., Q. Zhang, C. Nielsen, and K. He, 2011. An inventory of primary air pollutants and CO2 emissions from cement production in China, 1990-2020, Atmospheric Environment, 45(1): 147-154. https://doi.org/10.1016/j.atmosenv.2010.09.034
DOI
|
2 |
Mele, M. and C. Magazzino, 2020. A machine learning analysis of the relationship among iron and steel industries, air pollution, and economic growth in China, Journal of Cleaner Production, 277: 123293. https://doi.org/10.1016/j.jclepro.2020.123293
DOI
|
3 |
Jacobson, M. Z., 2009. Review of solutions to global warming, air pollution, and energy security, Energy & Environmental Science, 2(2): 148-173. https://doi.org/10.1039/B809990C
DOI
|
4 |
Jiang, P., Y. Chen, Y. Geng, W. Dong, B. Xue, B. Xu, and W. Li, 2013. Analysis of the co-benefits of climate change mitigation and air pollution reduction in China, Journal of Cleaner Production, 58: 130-137. https://doi.org/10.1016/j.jclepro.2013.07.042
DOI
|
5 |
Jung, H.S. and S. Lee, 2019. Special issue on machine learning techniques applied to geoscience information system and remote sensing, Applied Sciences, 9(12): 2446. https://doi.org/10.3390/app9122446
DOI
|
6 |
Lu, H., A. Yue, H. Chen, and R. Long, 2018. Could smog pollution lead to the migration of local skilled workers? Evidence from the Jing-Jin-Ji region in China, Resources, Conservation and Recycling, 130: 177-187. https://doi.org/10.1016/j.resconrec.2017.11.024
DOI
|
7 |
Kampa, M. and E. Castanas, 2008. Human health effects of air pollution, Environmental Pollution, 151(2): 362-367. https://doi.org/10.1016/j.envpol.2007.06.012
DOI
|
8 |
Kim, H. J., Q. Zhang, and Y. Sun, 2020. Measurement report: Characterization of severe spring haze episodes and influences of long-range transport in the Seoul metropolitan area in March 2019, Atmospheric Chemistry and Physics, 20(19): 11527-11550. https://doi.org/10.5194/acp-20-11527-2020
DOI
|
9 |
Li, Y., Y.H. Chiu, and L.C. Lu, 2018. Energy and AQI performance of 31 cities in China, Energy Policy, 122: 194-202. https://doi.org/10.1016/j.enpol.2018.07.037
DOI
|
10 |
Martin, M.J., D.E. Singh, J.C. Mourino, F.F. Rivera, R. Doallo, and J.D. Bruguera, 2003. High performance air pollution modeling for a power plant environment, Parallel Computing, 29(11-12): 1763-1790. https://doi.org/10.1016/j.parco.2003.05.018
DOI
|
11 |
Christenson, E. and M. Serre, 2015. Using remote sensing to calculate plant available nitrogen needed by crops on swine factory farm sprayfields in North Carolina, Proc. of SPIE Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, Toulouse, France, Sep. 21-24, vol. 9637, pp. 22-28. https://doi.org/10.1117/12.2195434
DOI
|
12 |
Baek, W.K. and H.S. Jung, 2021. Performance comparison of oil spill and ship classification from x-band dual-and single-polarized sar image using support vector machine, random forest, and deep neural network, Remote Sensing, 13(16): 3203. https://doi.org/10.3390/rs13163203
DOI
|
13 |
Pal, S., E. Ebrahimi, A. Zulfiqar, Y. Fu, V. Zhang, S. Migacz, D. Nellans, and P. Gupta, 2019. Optimizing multi-GPU parallelization strategies for deep learning training, IEEE Micro, 39(5): 91-101. https://doi.org/10.1109/mm.2019.2935967
DOI
|
14 |
Rajarathnam, U., V. Athalye, S. Ragavan, S. Maithel, D. Lalchandani, S. Kumar, E. Baum, C. Weyant, and T. Bond, 2014. Assessment of air pollutant emissions from brick kilns, Atmospheric Environment, 98: 549-553. https://doi.org/10.1016/j.atmosenv.2014.08.075
DOI
|
15 |
Redmon, J., S. Divvala, R. Girshick, and A. Farhadi, 2016. You only look once: Unified, real-time object detection, Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, Jun. 27-30, pp. 779-788. https://doi.org/10.1109/cvpr.2016.91
DOI
|
16 |
Brunekreef, B. and S. T. Holgate, 2002. Air pollution and health, The Lancet, 360(9341): 1233-1242. https://doi.org/10.1016/S0140-6736(02)11274-8
DOI
|
17 |
Borhani, F. and A. Noorpoor, 2020. Measurement of air pollution emissions from chimneys of production units moisture insulation (Isogam) Delijan, Journal of Environmental Science and Technology, 21(12): 57-71. https://doi.org/10.22034/JEST.2020.25934.3488
DOI
|
18 |
Chang, A., Y. Eo, S. Kim, Y. Kim, and Y. Kim, 2011. Canopy-cover thematic-map generation for Military Map products using remote sensing data in inaccessible areas, Landscape and Ecological Engineering, 7(2): 263-274. https://doi.org/10.1007/s11355-010-0132-1
DOI
|
19 |
Sportisse, B., 2007. A review of current issues in air pollution modeling and simulation, Computational Geosciences, 11(2): 159-181. https://doi.org/10.1007/s10596-006-9036-4
DOI
|
20 |
Diakogiannis, F.I., F. Waldner, P. Caccetta, and C. Wu, 2020. ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data, ISPRS Journal of Photogrammetry and Remote Sensing, 162: 94-114. https://doi.org/10.1016/j.isprsjprs.2020.01.013
DOI
|
21 |
Wei, W., X. Wang, H. Zhu, J. Li, S. Zhou, Z. Zou, and J.S. Li, 2017. Carbon emissions of urban power grid in Jing-Jin-Ji region: Characteristics and influential factors, Journal of Cleaner Production, 168: 428-440. https://doi.org/10.1016/j.jclepro.2017.09.015
DOI
|
22 |
Yao, Y., Z. Jiang, H. Zhang, B. Cai, G. Meng, and D. Zuo, 2017. Chimney and condensing tower detection based on faster R-CNN in high resolution remote sensing images, Proc. of 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, Jul. 23-28, pp. 3329-3332. https://doi.org/10.1109/igarss.2017.8127710
DOI
|
23 |
Shankar, K., Y. Zhang, Y. Liu, L. Wu, and C. H. Chen, 2020. Hyperparameter tuning deep learning for diabetic retinopathy fundus image classification, IEEE Access, 8: 118164-118173. https://doi.org/10.1109/ACCESS.2020.3005152
DOI
|
24 |
Dadboud, F., V. Patel, V. Mehta, M. Bolic, and I. Mantegh, 2021. Single-Stage UAV Detection and Classification with YOLOV5: Mosaic Data Augmentation and PANet, Proc. of 2021 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Nov. 16-19, pp. 1-8. https://doi.org/10.1109/AVSS52988.2021.9663841
DOI
|
25 |
Han, X., K. Choi, S. Bae, and H. Kwon, 2020. Relationship between chimney emissions and air pollutants near coal-fired power plants, ISEE Conference Abstracts, vol. 2020, no. 1. https://doi.org/10.1289/isee.2020.virtual.p-1033
DOI
|
26 |
Han, C., G. Li, Y. Ding, F. Yan, and L. Bai, 2020. Chimney detection based on faster R-CNN and spatial analysis methods in high resolution remote sensing images, Sensors, 20(16): 4353. https://doi.org/10.3390/s20164353
DOI
|
27 |
He, S. and L. Schomaker, 2019. DeepOtsu: Document enhancement and binarization using iterative deep learning, Pattern Recognition, 91: 379-390. https://doi.org/10.1016/j.patcog.2019.01.025
DOI
|
28 |
Huang, W., H. Wang, and Y. Wei, 2018. Endogenous or exogenous? examining trans-boundary air pollution by using the air quality index (aqi): A case study of 30 provinces and autonomous regions in china, Sustainability, 10(11): 4220. https://doi.org/10.3390/su10114220
DOI
|
29 |
Tang, L., X. Xue, J. Qu, Z. Mi, X. Bo, X. Chang, S. Wang, S. Li, W. Cui, and G. Dong, 2020. Air pollution emissions from Chinese power plants based on the continuous emission monitoring systems network, Scientific Data, 7(1): 1-10. https://doi.org/10.1038/s41597-020-00665-1
DOI
|
30 |
Wan, D.J., Z.X. Han, J.S. Yang, G.L. Yang, and X.Q. Liu, 2016. Heavy metal pollution in settled dust associated with different urban functional areas in a heavily air-polluted city in North China, International Journal of Environmental Research and Public Health, 13(11): 1119. https://doi.org/10.3390/ijerph13111119
DOI
|
31 |
Woo, J.H., C. Bu, J. Kim, Y.S. Ghim, and Y. Kim, 2018. Analysis of regional and inter-annual changes of air pollutants emissions in China, Journal of Korean Society for Atmospheric Environment, 34(1): 87-100 (in Korean with English abstract). https://doi.org/10.5572/KOSAE.2018.34.1.087
DOI
|
32 |
Jang. S.W., J.M. Baek, and M.S. Kang, 2021. A Combined Approach of Classification and Regression for Oriented Object Detection of Missiles, The Journal of Korean Institute of Electromagnetic Engineering and Science, 32(12): 1099-1107 (in Korean with English abstract). https://doi.org/10.5515/KJKIEES.2021.32.12.1099
DOI
|
33 |
Wu, W., H. Liu, L. Li, Y. Long, X. Wang, Z. Wang, J. Li, and Y. Chang, 2021. Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image, PLoS One, 16(10): e0259283. https://doi.org/10.1371/journal.pone.0259283
DOI
|
34 |
Zeng, Y., Y. Cao, X. Qiao, B.C. Seyler, and Y. Tang, 2019. Air pollution reduction in China: Recent success but great challenge for the future, Science of the Total Environment, 663: 329-337. https://doi.org/10.1016/j.scitotenv.2019.01.262
DOI
|
35 |
Zhang, H. and Q. Deng, 2019. Deep learning based fossil-fuel power plant monitoring in high resolution remote sensing images: A comparative study, Remote Sensing, 11(9): 1117. https://doi.org/10.1016/j.scitotenv.2019.01.262
DOI
|