Students Current Graduate Student
teachers Current Graduate Student
Kailun Jiang

Kailun Jiang

Date of Birth: October 19, 1996

Major: Agricultural Electrification and Automation

Grade: First year of PhD

School: College of Engineering, Huazhong Agricultural University

Research Direction: High-precision remote sensing inversion research of crop biological parameters



September 2023 - Present:   

PhD Agricultural Electrification and Automation, Huazhong Agricultural University

September 2022 - April 2023:

Algorithm Engineer Shanghai Central Motor Electronics

September 2019 - June 2022: 

Master Agricultural Electrification and Automation, Shenyang Agricultural University

September 2015 - June 2019: 

Bachelor Electronic Information Engineering, Shenyang Agricultural University


2019-2022: Participated in the key project of the Liaoning Provincial Department of Education: Research on the spatiotemporal inversion method of rice chlorophyll based on low-altitude remote sensing of drones.

My work:

Analyzed and processed the collected hyperspectral data and ground sample data.

Explored different red edge position extraction techniques to provide a solution to the red edge position problem in drone hyperspectral inversion.

Designed different feature selection and inversion model algorithms to achieve fast and accurate inversion of rice chlorophyll content.

Main research content:

1) Research on rice chlorophyll inversion based on hyperspectral red edge position extraction.

2) Research on rice chlorophyll content inversion based on drone hyperspectral remote sensing.

3) Research on spectral feature analysis and inversion of rice chlorophyll using RNCA-PSO-ELM.


Possess strong programming and algorithm skills, proficient in MATLAB and Python tools.

Have good English reading, writing, and expression abilities, CET6: 469, CET4: 505.

Good at paper writing, typesetting, and editing work, and have published multiple papers.

Have a background in computer-related knowledge, and have passed the national computer level3 examination.


[1]Cao Y , Jiang K , Wu J ,et al.Inversion modeling of japonica rice canopy chlorophyll content with UAV hyperspectral remote sensing[J].PLoS ONE, 2020, 15(9):e0238530.

[2]Jiang Kailun, An Jiqing, Zhao Yuwei, et al. Spectral Feature Analysis and Inversion of Rice Chlorophyll Using RNCA-PSO-ELM [J]. Journal of Agricultural Engineering, 2022, 38 (08): 178-186.

[3]Cao Yingli, Jiang Kailun, Liu Yadi, et al. Research on Rice Chlorophyll Inversion Based on Hyperspectral Red Edge Position Extraction [J]. Journal of Shenyang Agricultural University, 2021, 52 (06): 718-728.

[4]Cao Yingli, Jiang Kailun, Yu Zhengxin, et al. Rice Stripe Disease Detection and Identification Based on Deep Convolutional Neural Network [J]. Journal of Shenyang Agricultural University, 2020, 51 (05): 568-575.

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