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Shichao Jin
Researcher at Chinese Academy of Sciences
Publications - 35
Citations - 984
Shichao Jin is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Computer science & Lidar. The author has an hindex of 12, co-authored 22 publications receiving 351 citations. Previous affiliations of Shichao Jin include Nanjing Agricultural University.
Papers
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Journal ArticleDOI
Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms.
Shichao Jin,Yanjun Su,Shang Gao,Fangfang Wu,Tianyu Hu,Jin Liu,Wenkai Li,Dingchang Wang,Shaojiang Chen,Yuanxi Jiang,Yuanxi Jiang,Shuxin Pang,Qinghua Guo +12 more
TL;DR: The results showed that the method combing deep leaning and regional growth algorithms was promising in individual maize segmentation, and the values of r, p, and F of the three testing sites with different planting density were all over 0.9.
Journal ArticleDOI
Stem–Leaf Segmentation and Phenotypic Trait Extraction of Individual Maize Using Terrestrial LiDAR Data
TL;DR: A median normalized-vector growth (MNVG) algorithm, which can segment stem and leaf with four steps, i.e., preprocessing, stem growth, leaf growth, and postprocessing, is proposed, which may contribute to the study of LiDAR-based plant phonemics and precise agriculture.
Journal ArticleDOI
Evaluating maize phenotype dynamics under drought stress using terrestrial lidar
Yanjun Su,Fangfang Wu,Zurui Ao,Shichao Jin,Feng Qin,Boxin Liu,Shuxin Pang,Lingli Liu,Qinghua Guo +8 more
TL;DR: The results demonstrate the feasibility of using terrestrial lidar to monitor 3D maize phenotypes under drought stress in the field and may provide new insights on identifying the key phenotypes and growth stages influenced by drought stress.
Journal ArticleDOI
Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects
Shichao Jin,Xiliang Sun,Fangfang Wu,Yanjun Su,Yumei Li,Shiling Song,Kexin Xu,Qin Ma,Frédéric Baret,Frédéric Baret,Dong Jiang,Yanfeng Ding,Qinghua Guo +12 more
TL;DR: Three main challenges in lidar-based phenotypes development are identified: developing low cost, high spatial–temporal, and hyperspectral lidar facilities, moving into multi-dimensional phenotyping with an endeavor to generate new algorithms and models, and embracing open source and big data.
Journal ArticleDOI
An updated Vegetation Map of China (1:1000000)
Yanjun Su,Qinghua Guo,Tianyu Hu,Hongcan Guan,Shichao Jin,Shazhou An,Xuelin Chen,Ke Guo,Zhanqing Hao,Yuanman Hu,Yongmei Huang,Mingxi Jiang,Jiaxiang Li,Zhenji Li,Xiankun Li,Xiaowei Li,Cunzhu Liang,Renlin Liu,Qing Liu,Hongwei Ni,Shao-Lin Peng,Zehao Shen,Zhiyao Tang,Xingjun Tian,Xihua Wang,Ren-Qing Wang,Zongqiang Xie,Yingzhong Xie,Xiaoniu Xu,Xiaobo Yang,Yongchuan Yang,Lifei Yu,Ming Yue,Feng Zhang,Keping Ma +34 more
TL;DR: Wang et al. as discussed by the authors used a crowd-sourcing-change detection-classification-expert knowledge approach to update the Vegetation Map of China (1:1000000) generated in the 1980s.