中文版 | English

在结果中检索

IB-CAS

浏览/检索结果: 共4条，第1-4条 帮助

限定条件            
已选(0)清除 条数/页：   排序方式：
Application of deep learning in ecological resource research: Theories, methods, and challenges 期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2020, 卷号: 63, 期号: 10, 页码: 1457-1474
作者:  Guo, Qinghua;  Jin, Shichao;  Li, Min;  Yang, Qiuli;  Xu, Kexin;  Ju, Yuanzhen;  Zhang, Jing;  Xuan, Jing;  Liu, Jin;  Su, Yanjun;  Xu, Qiang;  Liu, Yu
Adobe PDF(4690Kb)  |  收藏  |  浏览/下载：105/0  |  提交时间：2022/03/01
Ecological resources  Deep learning  Neural network  Big data  Theory and tools  Application and challenge  
The Chromosome-Based Rubber Tree Genome Provides New Insights into Spurge Genome Evolution and Rubber Biosynthesis 期刊论文
MOLECULAR PLANT, 2020, 卷号: 13, 期号: 2, 页码: 336-350
作者:  Liu, Jin;  Shi, Cong;  Shi, Cheng-Cheng;  Li, Wei;  Zhang, Qun-Jie;  Zhang, Yun;  Li, Kui;  Lu, Hui-Fang;  Shi, Chao;  Zhu, Si-Tao;  Xiao, Zai-Yun;  Nan, Hong;  Yue, Yao;  Zhu, Xun-Ge;  Wu, Yu;  Hong, Xiao-Ning;  Fan, Guang-Yi;  Tong, Yan;  Zhang, Dan;  Mao, Chang-Li;  Liu, Yun-Long;  Hao, Shi-Jie;  Liu, Wei-Qing;  Lv, Mei-Qi;  Zhang, Hai-Bin;  Liu, Yuan;  Hu-tang, Ge-Ran;  Wang, Jin-Peng;  Wang, Jia-Hao;  Sun, Ying-Huai;  Ni, Shu-Bang;  Chen, Wen-Bin;  Zhang, Xing-Cai;  Jiao, Yuan-Nian;  Eichler, Evan E.;  Li, Guo-Hua;  Liu, Xin;  Gao, Li-Zhi
Adobe PDF(2390Kb)  |  收藏  |  浏览/下载：172/0  |  提交时间：2022/03/01
rubber tree  rubber biosynthesis  chromosome evolution  whole-genome duplication  domestication  
Estimation of degraded grassland aboveground biomass using machine learning methods from terrestrial laser scanning data 期刊论文
ECOLOGICAL INDICATORS, 2020, 卷号: 108
作者:  Xu, Kexin;  Su, Yanjun;  Liu, Jin;  Hu, Tianyu;  Jin, Shichao;  Ma, Qin;  Zhai, Qiuping;  Wang, Rui;  Zhang, Jing;  Li, Yumei;  Liu, Hon An;  Guo, Qinghua
Adobe PDF(4794Kb)  |  收藏  |  浏览/下载：93/0  |  提交时间：2022/03/01
Aboveground biomass (AGB)  Degraded grassland  Machine learning  Northern agro-pastoral ecotone  Terrestrial laser scanning (TLS)  
Retrieval of tree branch architecture attributes from terrestrial laser scan data using a Laplacian algorithm 期刊论文
AGRICULTURAL AND FOREST METEOROLOGY, 2020, 卷号: 284
作者:  Li, Yumei;  Su, Yanjun;  Zhao, Xiaoxia;  Yang, Mohan;  Hu, Tianyu;  Zhang, Jing;  Liu, Jin;  Liu, Min;  Guo, Qinghua
Adobe PDF(4327Kb)  |  收藏  |  浏览/下载：106/0  |  提交时间：2022/03/01
Trunk architecture  Laplacian algorithm  Dijkstra algorithm  Terrestrial laser scan data  Simulated data