Lirong Xiang

Wang, J., Hu, Y., Xiang, L., Morota, G., Brooks, S. A., Wickens, C. L., … Yu, H. (2024). Technical note: ShinyAnimalCV: open-source cloud-based web application for object detection, segmentation, and three-dimensional visualization of animals using computer vision. JOURNAL OF ANIMAL SCIENCE, 102. https://doi.org/10.1093/jas/skad416

Xiang, L., & Wang, D. (2023). [Review of A review of three-dimensional vision techniques in food and agriculture applications]. SMART AGRICULTURAL TECHNOLOGY, 5. https://doi.org/10.1016/j.atech.2023.100259

Lin, S., Li, J., Huang, D., Cheng, Z., Xiang, L., Ye, D., & Weng, H. (2023). Early Detection of Rice Blast Using a Semi-Supervised Contrastive Unpaired Translation Iterative Network Based on UAV Images. PLANTS-BASEL, 12(21). https://doi.org/10.3390/plants12213675

Xiang, L., Gai, J., Bao, Y., Yu, J., Schnable, P. S. S., & Tang, L. (2023, February 27). Field-based robotic leaf angle detection and characterization of maize plants using stereo vision and deep convolutional neural networks. JOURNAL OF FIELD ROBOTICS, Vol. 2. https://doi.org/10.1002/rob.22166

Wang, J., Xiang, L., Morota, G., Wickens, C., Cushon, E., Brooks, S., & Yu, H. (2023, November 6). Shinyanimalcv: Interactive Web Application for Object Detection and Three-Dimensional Visualization of Animals Using Computer Vision. JOURNAL OF ANIMAL SCIENCE, Vol. 101, pp. 244–245. https://doi.org/10.1093/jas/skad281.294

Gai, J., Wang, J., Xie, S., Xiang, L., & Wang, Z. (2023, November 13). Spectroscopic determination of chlorophyll content in sugarcane leaves for drought stress detection. PRECISION AGRICULTURE, Vol. 11. https://doi.org/10.1007/s11119-023-10082-0

Ye, S., Weng, H., Xiang, L., Jia, L., & Xu, J. (2023). Synchronously Predicting Tea Polyphenol and Epigallocatechin Gallate in Tea Leaves Using Fourier Transform-Near-Infrared Spectroscopy and Machine Learning. MOLECULES, 28(14). https://doi.org/10.3390/molecules28145379

Xiang, L., Liu, X., Raj, A., & Tang, L. (2022). Detection and characterization of maize plant architectural traits in the field using stereo vision and deep convolutional neural networks. 2022 ASABE Annual International Meeting. Presented at the 2022 ASABE Annual International Meeting, Houston, TX.

Liu, X., Xiang, L., Raj, A., & Tang, L. (2022). In-field soybean seed pod phenotyping on harvest stocks using 3D imaging and deep learning. 2022 ASABE Annual International Meeting. Presented at the 2022 ASABE Annual International Meeting, Houston, TX.

Xiang, L., Liu, X., Raj, A., Yu, J., Schnable, P. S., & Tang, L. (2022). Robotic Field-based Plant Architectural Traits Characterization Using Stereo Vision and Deep Neural Networks. Fourth International Workshop on Machine Learning for Cyber-Agricultural Systems (MLCAS2022). Presented at the Fourth International Workshop on Machine Learning for Cyber-Agricultural Systems (MLCAS2022), Ames, IA.

Wang, L., Xiang, L., Tang, L., & Jiang, H. (2021). A Convolutional Neural Network-Based Method for Corn Stand Counting in the Field. Sensors, 21(2), 507. https://doi.org/10.3390/s21020507

Xiang, L., Gai, J., Bao, Y., Yu, J., Schnable, P. S., & Tang, L. (2021). AngleNet: Leaf Angle Detection and Characterization of Maize Plants in the Field Based on Stereo Vision and Deep Convolutional Neural Network. 2021 ASABE Annual International Virtual Meeting. Presented at the 2021 ASABE Annual International Virtual Meeting.

Bao, Y., Gai, J., Xiang, L., & Tang, L. (2021). Field Robotic Systems for High-Throughput Plant Phenotyping: A Review and a Case Study. https://doi.org/10.1007/978-3-030-73734-4_2

Xiang, L., Tang, L., Gai, J., & Wang, L. (2021). Measuring Stem Diameter of Sorghum Plants in the Field Using a High-Throughput Stereo Vision System. Transactions of the ASABE, 64(6), 1999–2010. https://doi.org/10.13031/trans.14156

Xiang, L., Nolan, T. M., Bao, Y., Elmore, M., Tuel, T., Gai, J., … Tang, L. (2021). Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses. The Plant Journal, 107(6), 1837–1853. https://doi.org/10.1111/tpj.15401

Gai, J., Xiang, L., & Tang, L. (2021). Using a depth camera for crop row detection and mapping for under-canopy navigation of agricultural robotic vehicle. Computers and Electronics in Agriculture, 188, 106301. https://doi.org/10.1016/j.compag.2021.106301

Xiang, L., Gai, J., & Tang, L. (2020). Developing a high-throughput stereo vision system for plant phenotyping. Phenome 2020. Presented at the Phenome 2020, Tucson, AZ.

Gai, J., Tuel, T., Xiang, L., & Tang, L. (2020). Developing the Control System of an Autonomous Robot for Field-based Maize/Sorghum Plant Phenotyping. 2020 ASABE Annual International Virtual Meeting. Presented at the 2020 ASABE Annual International Virtual Meeting.

Gai, J., Tuel, T., Xiang, L., & Tang, L. (2020). PhenoBot 3.0 - an Autonomous Robot for Field-based Maize/Sorghum Plant Phenotyping. Phenome 2020. Presented at the Phenome 2020, Tucson, AZ.

Xiang, L., Tang, L., Gai, J., & Wang, L. (2020). PhenoStereo: a high-throughput stereo vision system for field-based plant phenotyping - with an application in sorghum stem diameter estimation. 2020 ASABE Annual International Virtual Meeting, July 13-15, 2020. Presented at the 2020 ASABE Annual International Virtual Meeting, July 13-15, 2020. https://doi.org/10.13031/aim.202001190

Xiang, L., Bao, Y., Tang, L., Ortiz, D., & Salas-Fernandez, M. G. (2019). Automated morphological traits extraction for sorghum plants via 3D point cloud data analysis. Computers and Electronics in Agriculture, 162, 951–961. https://doi.org/10.1016/j.compag.2019.05.043

Xiang, L., Bao, Y., Nolan, T., Yin, Y., & Tang, L. (2019). Robotic imaging-based methods for leaf segmentation and growth tracking in Arabidopsis. 2019 ASABE Annual International Meeting. Presented at the 2019 ASABE Annual International Meeting, Boston, MA.

Xiang, L., Bao, Y., Tang, L., & Salas-Fernandez, M. G. (2018). Automated morphological trait extraction for sorghum plants via 3D point cloud data analysis. 2018 ASABE Annual International Meeting. Presented at the 2018 ASABE Annual International Meeting, Detroit, MI.

Hu, Y., Wang, L., Xiang, L., Wu, Q., & Jiang, H. (2018). Automatic Non-Destructive Growth Measurement of Leafy Vegetables Based on Kinect. Sensors, 18(3), 806. https://doi.org/10.3390/s18030806

Xiang, L. R., Ma, Z. H., Zhao, X. Y., Liu, F., He, Y., & Feng, L. (2017). Comparative Analysis of Chemometrics Method on Heavy Metal Detection in Soil with Laser-Induced Breakdown Spectroscopy. Spectroscopy and Spectral Analysis, 37(12), 3871–3876. Retrieved from http://www.gpxygpfx.com/EN/Y2017/V37/I12/3871