1 |
Ministry of Housing and Urban Rural Development of the People's Republic of China. Load Code for Building Structures [S]. Beijing: China Architecture & Building Press, 2012. [中华人民共和国住房和城乡建设部. 建筑结构荷载规范[S]. 北京: 中国建筑工业出版社, 2012.]
|
2 |
Strategic Alliance for Technological Innovation of China's Construction Waste Resource Industry. Report on the Development of China's Construction Waste Resource Industry[R]. Beijing: 2014.中国建筑垃圾资源化产业技术创新战略联盟. 中国建筑垃圾资源化产业发展报告[R]. 北京: 2014.
|
3 |
Zhao Jun, Liu Qiuxia, Lin Liqing, et.al. Evolution and Comparison of Construction Waste Generation Characteristics in Big Cities[J]. Journal of Central South University(Natural Science Edition), 2013, 44(3):1297-1304.
|
3 |
赵军,刘秋霞,林立清, 等.大城市建筑垃圾产生特征演变及比较[J]. 中南大学学报(自然科学版), 2013, 44(3): 1297-1304.
|
4 |
Lu Zhongyi. Exploration on the Utilization of Urban Construction Waste [J]. Shanxi Architecture,2019, 45(6): 183-184.
|
4 |
卢忠义.城市建筑垃圾资源化利用探讨[J].山西建筑,2019,45(6):183-184.
|
5 |
Yang X N. Study on Environmental Impact Assessment of Construction Waste[J]. Chemical Intermediate, 2015, 11(10): 109-110.
|
5 |
杨小宁. 关于建筑垃圾的环境影响评价研究[J]. 化工中间体, 2015, 11(10): 109-110.
|
6 |
Li Yilong. Brief Analysis of Environmental Pollution Hazards and Management Measures of Construction Waste under the Background of Urbanization[J]. Green Building Materials, 2018(3): 19-20.
|
6 |
李熠茏. 浅析城镇化背景下建筑垃圾对于环境的污染危害及管理措施[J]. 绿色环保建材, 2018(3): 19-20.
|
7 |
He Jiayan. Beijing Speeds up the Recycling of Construction Waste [J].Invest in Beijing, 2018(6): 35-36.
|
7 |
何佳艳. 北京提速建筑垃圾资源化处理[J]. 投资北京, 2018(6): 35-36.
|
8 |
Zhikang B, Weisheng L. Developing Efficient Circularity for Construction and Demolition Waste Management in Fast Emerging Economies: Lessons Learned from Shenzhen, China[J]. Science of the Total Environment, 2020, 724. doi:10.1016/j.scitotenv.2020.138264.
doi: 10.1016/j.scitotenv.2020.138264
|
9 |
Bagheri S, Hordon R M. Hazardous Waste Site Identification Using Aerial Photography: A Pilot Study in Burlington County, New Jersey, USA[J]. Environmental Management, 1988, 12(3): 411-412. doi: 10.1007/BF01867531.
doi: 10.1007/BF01867531
|
10 |
Wu Wenwei, Liu Jing. Application of Remote Sensing Technology in the Investigation of Solid Waste Distribution in Beijing[J]. Environmental Health Engineering, 2000(2): 76-78.
|
10 |
吴文伟,刘竞. 北京市固体废弃物分布调查中遥感技术的应用[J]. 环境卫生工程, 2000(2): 76-78.
|
11 |
Liu Yalan, Ren Yuhuan, Wei Chengjie, et al. Applied Research on the Monitoring of Irregular Garbage Dumps by Beijing No.1 Small Satellite[J]. Journal of Remote Sensing, 2009, 13(2): 320-326.
|
11 |
刘亚岚, 任玉环, 魏成阶,等. 北京1号小卫星监测非正规垃圾场的应用研究[J]. 遥感学报, 2009, 13(2): 320-326.
|
12 |
Liang W H, Liu J K, Chen Q, et al. Comparative Analysis of Extraction of Eucalyptus Information from GF-2 Image based on Object-oriented Method[J]. Forestry Resource Management, 2017 (6): 54-59.梁文海, 刘吉凯, 陈琦等. 基于面向对象方法的GF-2影像桉树信息提取对比分析[J]. 林业资源管理, 2017(6): 54-59.
|
13 |
Qin Haichun. Research on Urban Domestic Refuse Monitoring Method based on High-resolution Remote Sensing Images Made in China[J]. China Construction Informatization, 2016 (4): 75-77.
|
13 |
秦海春. 基于国产高分遥感影像的城镇生活垃圾监管方法研究[J]. 中国建设信息化, 2016(4): 75-77.
|
14 |
Huang Huiling, Han Jun, Wu Feibin, et al. Study on Color Feature Extraction and Classification of Construction Waste[J]. Optical and Optoelectronic Technology, 2018,16(1):53-57.
|
14 |
黄惠玲, 韩军, 吴飞斌, 等. 建筑垃圾的颜色特征提取与分类研究[J]. 光学与光电技术, 2018,16(1):53-57.
|
15 |
Li H K, Xu F, Li Q. Remote Sensing Monitoring of Land Damage and Restoration in Rare Earth Mining Areas in 6 Counties in Southern Jiangxi based on Multisource Sequential Images[J]. Journal of Environmental Management, 2020, 267. doi:10.1016/j.jenvman.2020.110653.
doi: 10.1016/j.jenvman.2020.110653
|
16 |
Lecun Y, Boser B, Denker J S, et al. Backpropagation Applied to Handwritten Zip Code Recognition[J]. Neural Computation,1989,1(4):541-551.doi:10.1162/neco.1989.1.4. 541.
doi: 10.1162/neco.1989.1.4. 541
|
17 |
Rebecca G, Tim D, Warwick H, et al. A Remote Sensing Approach to Mapping Fire Severity in South-eastern Australia Using Sentinel 2 and Random Forest[J]. Remote Sensing of Environment, 2020, 240. doi: 10.1016/j.rse.2020.111702.
doi: 10.1016/j.rse.2020.111702
|
18 |
Zheng Zongsheng, Hu Chenyu, Huang Dongmei, et al. Research on Transfer Learning Methods for Classification of Typhoon Cloud Image[J]. Remote Sensing Technology and Application, 2020 ,35(1): 202-210.
|
18 |
郑宗生,胡晨雨,黄冬梅, 等. 基于迁移学习及气象卫星云图的台风等级分类研究[J]. 遥感技术与应用, 2020 ,35(1): 202-210.
|
19 |
Wang Xin, Li Ke, Mingjun Xv, et al. An Improved Remote Sensing Image Classification Method based on Depth Learning[J]. Computer Applications, 2019, 32(2): 382-387.
|
19 |
王鑫, 李可, 徐明君, 等. 改进的基于深度学习的遥感图像分类方法[J]. 计算机应用, 2019, 32(2):382-387.
|
20 |
Huang Z M, Cheng G L, Wang H Z, et al. Building Extraction from Multi-source Remote Sensing Images via Deep Deconvolution Neural Networks[C]∥IEEE International Geoscience and Remote Sensing Symposium. Beijing, 2016. doi: 10.1109/IGARSS.2016.7729471.
doi: 10.1109/IGARSS.2016.7729471
|
21 |
Zheng Yuanpan, Li Guangyang, Li Ye. Review on the Application of Deep Learning in Image Recognition [J]. Computer Engineering and Applications, 2019, 55 (12): 20-36.
|
21 |
郑远攀, 李广阳, 李晔. 深度学习在图像识别中的应用研究综述[J].计算机工程与应用, 2019, 55(12): 20-36.
|
22 |
Lin Y Z, Zhang B M, Xu J F, et al. Building Extraction from High Resolution Remote Sensing Images based on Multi-features and Multi-scales[J]. Surveying and Mapping Bulletin, 2017(12):53-57.林雨准,张保明,徐俊峰,等.多特征多尺度相结合的高分辨率遥影像建筑物提取[J]. 测绘通报,2017(12):53-57.
|
23 |
Gao Yang. Building Extraction from High Resolution Remote Sensing Images based on Convolutional Neural Network [D]. Nanjing:Nanjing University, 2018.
|
23 |
高扬.基于卷积神经网络的高分辨率遥感影像建筑物提取[D].南京:南京大学, 2018.
|
24 |
Yang Zhenzhen, Kuang Nan, Fan Lu, et al. An Overview of Image Classification Algorithms based on Convolutional Neural Networks[J]. Signal Processing, 2018, 34(12): 1474-1489.
|
24 |
杨真真, 匡楠, 范露,等.基于卷积神经网络的图像分类算法综述[J]. 信号处理, 2018, 34(12): 1474-1489.
|
25 |
Wu Zhengwen. Application of Convolutional Neural Network in Image Classification[D]. Chengdu: University of Electronic Science and Technology, 2015.
|
25 |
吴正文.卷积神经网络在图像分类中的应用研究[D].成都:电子科技大学, 2015.
|
26 |
Zhao Xujiang. Remote Sensing Image Target Detection and Recognition based on Convolution Neural Network[D]. Beijing:China University of Science and Technology, 2018.
|
26 |
赵旭江. 基于卷积神经网络的遥感图像目标检测与识别[D].北京:中国科学技术大学, 2018.
|
27 |
Lin Yu, Chen Xiaoyong. Research on Road Traffic Sign Recognition based on Inception V3 Model[J]. Jiangxi Science, 2018, 36(5): 849-852.
|
27 |
林宇, 陈晓勇. 基于Inception V3模型的道路交通标志识别研究[J]. 江西科学, 2018, 36(5): 849-852.
|
28 |
Abadi M, Agarwal A, Barham P, et al. Tensor Flow: Large-Scale Machine Learning on Heterogeneous Distributed Systems[J]. Preliminary White Paper,2016,9:1-19.
|
29 |
Saxena A. Convolutional Neural Networks: An Illustration in Tensor Flow[J]. Crossroads, 2016, 22(4): 56-58. doi: 10.1145/2951024.
doi: 10.1145/2951024
|
30 |
Szegedy C, Vanhoucke V, Ioffe S, et al. Rethinking the Inception Architecture for Computer Vision[J].Computer Science, 2015: 2818 -2826. doi:10.1109/CVPR.2016.308.
doi: 10.1109/CVPR.2016.308
|
31 |
Angelova A, Zhu S. Efficient Object Detection and Segmentation for Fine-grained Recognition[J].IEEE Conference on Computer Vision and Pattern Recognition, 2013: 9(4): 811-81. doi: 10.1109/cvpr.2013.110.
doi: 10.1109/cvpr.2013.110
|
32 |
Lu K A. Current Situation and Comprehensive Utilization of Construction Waste in China[J]. Construction Technique, 2005, 28(6):15-16.
|
32 |
陆凯安. 我国建筑垃圾的现状与综合利用[J]. 施工技术, 2005, 28(6):15-16.
|