Lirong Xiang

Assistant Professor

Dr. Xiang is the Principal Investigator of the Automation and Robotics Lab in the Department of Biological and Agricultural Engineering at North Carolina State University and affiliated with N.C. Plant Sciences Initiative and Department of Electrical and Computer Engineering. She received her Ph.D. degree in Agricultural and Biosystems Engineering from Iowa State University and her B.S. degree in Biosystems Engineering from Zhejiang University. Dr. Xiang works on agricultural robotics, 2D & 3D computer vision, and machine learning. During her Ph.D. program, she has developed robotic and automated systems for both indoor and in-field plant phenotyping applications. Dr. Xiang joined BAE in August 2022.

Education

B.S. 2017

Biosystems Engineering

Zhejiang University, China

Ph.D. 2022

Agricultural and Biosystems Engineering

Iowa State University, USA

Research Description

Dr. Xiang's research mainly focuses on developing smart cyber-physical systems that integrate cutting-edge robotics, machine vision, and machine learning technologies to automate labor-intensive tasks in agricultural systems. The research topics include but are not limited to: developing robotic platforms for weeding, transplanting, and selective harvesting; adopting AI and robotics tools for precision livestock management; and combining aerial and ground robots for in-situ and non-invasive crop sensing.

Publications

Plant-Denoising-Net (PDN): A plant point cloud denoising network based on density gradient field learning
Wu, J., Xiang, L., You, H., Tang, L., & Gai, J. (2024), ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 210, 282–299. https://doi.org/10.1016/j.isprsjprs.2024.03.010
Swin-Roleaf: A new method for characterizing leaf azimuth angle in large-scale maize plants
He, W., Gage, J. L., Rellán-Álvarez, R., & Xiang, L. (2024), Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2024.109120
Technical note: ShinyAnimalCV: open-source cloud-based web application for object detection, segmentation, and three-dimensional visualization of animals using computer vision
Wang, J., Hu, Y., Xiang, L., Morota, G., Brooks, S. A., Wickens, C. L., … Yu, H. (2024), JOURNAL OF ANIMAL SCIENCE, 102. https://doi.org/10.1093/jas/skad416
A review of three-dimensional vision techniques in food and agriculture applications
Xiang, L., & Wang, D. (2023). [Review of , ]. SMART AGRICULTURAL TECHNOLOGY, 5. https://doi.org/10.1016/j.atech.2023.100259
Early Detection of Rice Blast Using a Semi-Supervised Contrastive Unpaired Translation Iterative Network Based on UAV Images
Lin, S., Li, J., Huang, D., Cheng, Z., Xiang, L., Ye, D., & Weng, H. (2023), PLANTS-BASEL, 12(21). https://doi.org/10.3390/plants12213675
Field-based robotic leaf angle detection and characterization of maize plants using stereo vision and deep convolutional neural networks
Xiang, L., Gai, J., Bao, Y., Yu, J., Schnable, P. S. S., & Tang, L. (2023, February 27), JOURNAL OF FIELD ROBOTICS, Vol. 2. https://doi.org/10.1002/rob.22166
Shinyanimalcv: Interactive Web Application for Object Detection and Three-Dimensional Visualization of Animals Using Computer Vision
Wang, J., Xiang, L., Morota, G., Wickens, C., Cushon, E., Brooks, S., & Yu, H. (2023, November 6), JOURNAL OF ANIMAL SCIENCE, Vol. 101, pp. 244–245. https://doi.org/10.1093/jas/skad281.294
Spectroscopic determination of chlorophyll content in sugarcane leaves for drought stress detection
Gai, J., Wang, J., Xie, S., Xiang, L., & Wang, Z. (2023, November 13), PRECISION AGRICULTURE, Vol. 11. https://doi.org/10.1007/s11119-023-10082-0
Synchronously Predicting Tea Polyphenol and Epigallocatechin Gallate in Tea Leaves Using Fourier Transform-Near-Infrared Spectroscopy and Machine Learning
Ye, S., Weng, H., Xiang, L., Jia, L., & Xu, J. (2023), MOLECULES, 28(14). https://doi.org/10.3390/molecules28145379
Detection and characterization of maize plant architectural traits in the field using stereo vision and deep convolutional neural networks
Xiang, L., Liu, X., Raj, A., & Tang, L. (2022), 2022 ASABE Annual International Meeting. Presented at the 2022 ASABE Annual International Meeting, Houston, TX.

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Grants

Precision Agriculture Technologies for Cotton Seed Damage Detection
Cotton, Inc.(1/01/23 - 12/31/24)
Precision Agriculture Technologies for Cotton Production in North Carolina
Cotton, Inc.(1/01/12 - 12/31/24)