Professor | 金时超 | 数字化转型顾问

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Name	金时超
Contact Information	njschaon@njau.edu.cn
Language ability	中文, 英语
Province	江苏

Upload Avatar (500 x 500)

Name

金时超

Contact Information

njschaon@njau.edu.cn

Language ability

中文, 英语

Province

江苏

University/Lab Affiliation and Title	南京农业大学
Faculty	academy for adyanced interdisciplinary studies
Academic Background & Achievements	2016.9–2020.6 理学博士: 中国科学院大学搭建了多源遥感表型观测平台（Crop3D+）在ISPRS J PHOTOGRAMM、Plant Communications, IEEE TGRS等杂志发表论文41篇
Work Experience	2020.9-至今 - 南京农业大学 - 副教授 2020.7-2020.9 - 南京农业大学 - 副教授（高层次人才引进）
Awards	2020: 江苏省“双创博士” 2019: 全国激光遥感与探测前沿博士生学术会议优秀青年报告奖，北京大学 2018: 第二届国际研究生学术论坛一等奖(1/800)，植物研究所

University/Lab Affiliation and Title

南京农业大学

Faculty

academy for adyanced interdisciplinary studies

Academic Background & Achievements

2016.9–2020.6 理学博士: 中国科学院大学
搭建了多源遥感表型观测平台（Crop3D+）
在ISPRS J PHOTOGRAMM、Plant Communications, IEEE TGRS等杂志发表论文41篇

Work Experience

2020.9-至今 - 南京农业大学 - 副教授
2020.7-2020.9 - 南京农业大学 - 副教授（高层次人才引进）

Awards

2020: 江苏省“双创博士”
2019: 全国激光遥感与探测前沿博士生学术会议优秀青年报告奖，北京大学
2018: 第二届国际研究生学术论坛一等奖(1/800)，植物研究所

Areas of Focus	以遥感和深度学习为核心的植物表型技术创新集成多元传感技术的高通量表型平台建设面向智慧育种和精准栽培的表型-基因-环境交叉研究
Publications	Deciphering the contributions of spectral and structural data to wheat yield estimation from proximal sensing., Li Qing, Jin Shichao, Zang Jingrong, Wang Xiao, Sun Zhuangzhuang, Li Ziyu, Xu Shan, Ma Qin, Su Yanjun, Guo Qinghua, Jiang Dong, 2022 Proximal and remote sensing in plant phenomics: Twenty years of progress, challenges and perspectives., Tao Haiyu, Xu Shan, Tian Yongchao, Li Zhaofeng, Ge Yan, Zhang Jiaoping, Wang Yu, Zhou Guodong, Deng Xiong, Zheng Ze, Ding Yanfeng, Jiang Dong, Guo Qinghua, Jin Shichao, 2022 PlantNet: A dual-function point cloud segmentation network for multiple plant species., Li Dawei, Shi Guoliang, Li Jinsheng, Chen Yingliang, Zhang Songyin, Xiang Shiyu, Jin Shichao, 2022 Simultaneous Prediction of Wheat Yield and Grain Protein Content Using Multitask Deep Learning from Time-Series Proximal Sensing., Sun Zhuangzhuang., Li Qing, Jin Shichao, Song Yunlin, Xu Shan, Wang Xiao, Cai Jian, Zhou Qin, Ge Yan, Zhang Ruinan, Zang Jingrong, Jiang Dong, 2022 Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series., Jin Shichao, Su Yanjun, Zhang Yongguang, Song Shilin, Li Qing, Liu Zhonghua, Ma Qin, Ge Yan, Liu LingLi, Ding Yanfeng, Baret Frédéric, Guo Qinghua, 2021 Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects., Jin Shichao, Sun Xiliang, Wu Fangfang, Su Yanjun, Li Yumei, Song Shiling, Xu Kexin, Ma Qin, Baret Frédéric, Jiang Dong, Ding Yanfeng, Guo Qinghua, 2021 Separating the structural components of maize for field phenotyping using terrestrial lidar data and deep convolutional neural networks., Jin Shichao, Su Yanjun, Gao Shang, Wu Fangfang, Ma Qin, Xu Kexin, Ma Qin, Hu Tianyu, Liu Jin, Pang ShuXin, Guan Hongcan, Zhang Jing, Guo Qinghua, 2020 Stem-Leaf Segmentation and Phenotypic Trait Extraction of Individual Maize Using Terrestrial LiDAR Data., Jin Shichao, Su Yanjun, Wu Fangfang, Pang ShuXin, Gao Shang, Hu Tianyu, Liu Jin, Guo Qinghua, 2019 Non-destructive estimation of field maize biomass using terrestrial lidar: An evaluation from plot level to individual leaf level., Jin Shichao, Su Yanjun, Song Shilin, Xu Kexin, Hu Tianyu, Yang Qiuli, Wu Fangfang, Xu Guangcai, Ma Qin, Guan Hongcan, Pang Shuxin, Li Yumei, Guo Qinghua, 2020 Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms., Jin Shichao, Su Yanjun, Gao Shang, Wu Fangfang, Hu Tianyu, Liu Jin, Li Wenkai, Wang Dingchang, Chen Shaojiang, Jiang Yuanxi, Pang Shuxin, Guo Qinghua, 2018 A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments., Jin Shichao, Su Yanjun, Zhao Xiaoqian, Hu Tianyu, Guo Qinghua, 2020 The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data., Jin Shichao, Su Yanjun, Gao Shang, Hu Tianyu, Liu Jin, Guo Qinghua, 2018 Application of deep learning in ecological resource research: Theories, methods, and challenges., Guo Qinghua, Jin Shichao, Li Min, Yang Qiuli, Xu Kexin, Ju Yuanzhen, Zhang Jing, Xuan Jing, Liu Jin, Su Yanjun, Xu Qiang, Liu Yu, 2020 “绿途”系统：公民科学时代的植被调查制图新工具., 金时超, 胡天宇, 苏艳军, 马勤, 关宏灿, 杨默含, 郭庆华, 2021 高通量作物表型监测: 育种和精准农业发展的加速器., 郭庆华, 杨维才, 吴芳芳, 庞树鑫, 金时超, 陈凡, 王秀杰, 2018

Areas of Focus

以遥感和深度学习为核心的植物表型技术创新
集成多元传感技术的高通量表型平台建设
面向智慧育种和精准栽培的表型-基因-环境交叉研究

Publications

Deciphering the contributions of spectral and structural data to wheat yield estimation from proximal sensing., Li Qing, Jin Shichao*, Zang Jingrong, Wang Xiao, Sun Zhuangzhuang, Li Ziyu, Xu Shan, Ma Qin, Su Yanjun, Guo Qinghua, Jiang Dong*, 2022
Proximal and remote sensing in plant phenomics: Twenty years of progress, challenges and perspectives., Tao Haiyu, Xu Shan, Tian Yongchao, Li Zhaofeng, Ge Yan, Zhang Jiaoping, Wang Yu, Zhou Guodong, Deng Xiong, Zheng Ze, Ding Yanfeng, Jiang Dong, Guo Qinghua, Jin Shichao*, 2022
PlantNet: A dual-function point cloud segmentation network for multiple plant species., Li Dawei, Shi Guoliang, Li Jinsheng, Chen Yingliang, Zhang Songyin, Xiang Shiyu, Jin Shichao*, 2022
Simultaneous Prediction of Wheat Yield and Grain Protein Content Using Multitask Deep Learning from Time-Series Proximal Sensing., Sun Zhuangzhuang., Li Qing, Jin Shichao*, Song Yunlin, Xu Shan, Wang Xiao, Cai Jian, Zhou Qin, Ge Yan, Zhang Ruinan, Zang Jingrong, Jiang Dong*, 2022
Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series., Jin Shichao*, Su Yanjun, Zhang Yongguang, Song Shilin, Li Qing, Liu Zhonghua, Ma Qin, Ge Yan, Liu LingLi, Ding Yanfeng, Baret Frédéric, Guo Qinghua, 2021
Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects., Jin Shichao*, Sun Xiliang, Wu Fangfang, Su Yanjun, Li Yumei, Song Shiling, Xu Kexin, Ma Qin, Baret Frédéric, Jiang Dong, Ding Yanfeng, Guo Qinghua, 2021
Separating the structural components of maize for field phenotyping using terrestrial lidar data and deep convolutional neural networks., Jin Shichao, Su Yanjun, Gao Shang, Wu Fangfang, Ma Qin, Xu Kexin, Ma Qin, Hu Tianyu, Liu Jin, Pang ShuXin, Guan Hongcan, Zhang Jing, Guo Qinghua, 2020
Stem-Leaf Segmentation and Phenotypic Trait Extraction of Individual Maize Using Terrestrial LiDAR Data., Jin Shichao, Su Yanjun, Wu Fangfang, Pang ShuXin, Gao Shang, Hu Tianyu, Liu Jin, Guo Qinghua, 2019
Non-destructive estimation of field maize biomass using terrestrial lidar: An evaluation from plot level to individual leaf level., Jin Shichao, Su Yanjun, Song Shilin, Xu Kexin, Hu Tianyu, Yang Qiuli, Wu Fangfang, Xu Guangcai, Ma Qin, Guan Hongcan, Pang Shuxin, Li Yumei, Guo Qinghua, 2020
Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms., Jin Shichao, Su Yanjun, Gao Shang, Wu Fangfang, Hu Tianyu, Liu Jin, Li Wenkai, Wang Dingchang, Chen Shaojiang, Jiang Yuanxi, Pang Shuxin, Guo Qinghua, 2018
A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments., Jin Shichao, Su Yanjun, Zhao Xiaoqian, Hu Tianyu, Guo Qinghua, 2020
The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data., Jin Shichao, Su Yanjun, Gao Shang, Hu Tianyu, Liu Jin, Guo Qinghua, 2018
Application of deep learning in ecological resource research: Theories, methods, and challenges., Guo Qinghua, Jin Shichao, Li Min, Yang Qiuli, Xu Kexin, Ju Yuanzhen, Zhang Jing, Xuan Jing, Liu Jin, Su Yanjun, Xu Qiang, Liu Yu, 2020
“绿途”系统：公民科学时代的植被调查制图新工具., 金时超, 胡天宇, 苏艳军, 马勤, 关宏灿, 杨默含, 郭庆华, 2021
高通量作物表型监测: 育种和精准农业发展的加速器., 郭庆华, 杨维才, 吴芳芳, 庞树鑫, 金时超, 陈凡, 王秀杰, 2018

遥感深度学习植物表型多传感器技术高通量表型-基因-环境智慧育种精准栽培创新交叉研究

周济 - 南京农业大学

Area of Focus
表型组学 | 人工智能 | 基因组学 | 育种 | 作物 | 数据融合 | 机器学习 | 遥感 | 农业 | 创新

李英伦 - 南京农业大学

Frédéric Baret - 南京农业大学

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