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Huajian Liu

Huajian Liu
School of Agriculture, Food and Wine
Faculty of Sciences

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Huajian Liu

Research direction: plant phenotyping, applications of machine learning, deep learning, optical sensing system design, bio-inspired machine vision system, bird vision, insect vision, high-dimensional colour space, multispectral and hyperspectral image processing, 3D model reconstruction and object recognition, insect/plant detection, machine vision for agricultural applications

Journals

Year Citation
2018 Liu, H., Lee, S. -H., & Chahl, J. (2018). Registration of multispectral 3D points for plant inspection. Precision Agriculture, 19(3), 513-536.
DOI
2018 Liu, H., & Chahl, J. (2018). A multispectral machine vision system for invertebrate detection on green leaves. Computers and Electronics in Agriculture, 150, 279-288.
DOI
2017 Liu, H., Lee, S. -H., & Chahl, J. S. (2017). A review of recent sensing technologies to detect invertebrates on crops. Precision Agriculture, 18(4), 635-666.
DOI
2017 Liu, H., Lee, S. -H., & Chahl, J. S. (2017). An evaluation of the contribution of ultraviolet in fused multispectral images for invertebrate detection on green leaves. Precision Agriculture, 18(4), 667-683.
DOI
2017 Liu, H., Lee, S. -H., & Chahl, J. S. (2017). A multispectral 3-D vision system for invertebrate detection on crops. IEEE Sensors Journal, 17(22), 7502-7515.
DOI
2017 Liu, H., Lee, S. -H., & Chahl, J. S. (2017). Transformation of a high-dimensional color space for material classification. Journal of the Optical Society of America A, 34(4), 523.
DOI
2016 Liu, Y., Ran, R., Hu, C., Cui, B., Xu, Y., Liu, H., . . . Shi, J. (2016). The metabolic responses of HepG2 cells to the exposure of mycotoxin deoxynivalenol. World Mycotoxin Journal, 9(4), 577-586.
DOI Scopus3 WoS4
2014 Liu. (2014). DEVELOPMENT OF A MACHINE VISION SYSTEM FOR WEED DETECTION DURING BOTH OF OFF-SEASON AND IN-SEASON IN BROADACRE NO-TILLAGE CROPPING LANDS. American Journal of Agricultural and Biological Sciences, 9(2), 174-193.
DOI
2013 Liu. (2013). DEVELOPMENT OF A PROXIMAL MACHINE VISION SYSTEM FOR OFF-SEASON WEED MAPPING IN BROADACRE NO-TILLAGE FALLOWS. Journal of Computer Science, 9(12), 1803-1821.
DOI

Conference Papers

Year Citation
2018 Liu, H. (2018). Bioinspired invertebrate pest detection on standing crops. In Bioinspiration, Biomimetics, and Bioreplication VIII. Colorado, United States.
DOI
2015 Liu, H., & Lee, S. (2015). Stitching of video sequences for weed mapping. In 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP) (pp. 441-444). Online: IEEE.
DOI
2013 Liu, H. (2013). Development of a green plant image segmentation method of machine vision system for no-tillage fallow weed detection. In innovative agricultural technologies for a sustainable futur. Mandurah, WA, Australia.
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