top of page
此網站是使用
.com
網站幫手設計的。立即用來製作您的網站吧！立即開始

Professor

Shih Fang Chen
陳世芳

Associate Professor

     Department of Biomechatronics Engineering,

National Taiwan University

+886-2-3366-5354

Education

Ph.D - Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, USA
M.S. - Bio-lndustrial Mechatronics Engineering, National Taiwan University, Taiwan
B.S.  - Bio-lndustrial Mechatronics Engineering, National Taiwan University, Taiwan

Work experience

Postdoctoral Fellow - Research Center for Applied Sciences, Academia Sinica 
                                      Department of Physics, National Taiwan University
Postdoctoral Researcher - ADM Institute for the Prevention of Postharvest Loss, 
                                              University of Illinois at Urbana-Champaign
Postdoctoral Researcher - Energy Biosciences Institute, University of Illinois at Urbana-Champaign

Research Focus

Smart/Precision Agriculture
Image Processing
Machine/Deep Learning Algorithm
Near-Infrared/Fourier-transform infrared/Raman Spectroscopy
Chemometrics/Multivariate Analysis
Flavor Analysis

Publications

Journal Papers

  • Chang, Y.T., Hung, S.P., Lu, C.C., Peng, J.H., & Chen, S.F. 2021. Prediction of specialty coffee flavors based on near-infrared spectra using machine and deep learning methods. Journal of the Science of Food and Agriculture, 101(11): 4705-4714.

  • Xie, J. H., & Chen, S. F. 2021. Feasibility assessment of applying surface-enhanced Raman spectroscopy (SERS) for detecting carbendazim in astragalus. Journal of the Agricultural Association of Taiwan, 21(3): 165-181.

  • Chen, Y. T., & Chen, S. F. 2020. Localizing plucking points of tea leaves using deep convolutional neural networks. Computers and Electronics in Agriculture, 171, 105298.

  • Lee, S. H., Lin, S. R., & Chen, S. F. 2020. Identification of Tea Foliar Diseases and Pest Damages under Practical Field Conditions Using Convolutional Neural Network. Plant Pathology 2020(00): 1– 9.

  • Xie, J. H., & Chen, S. F. 2020. Discrimination of geographical origins for astragalus and angelica using vibrational spectroscopies. Journal of the Agricultural Association of Taiwan, 21(1): 34-54. (In Chinese)

  • Liao, M. S., Chen, S.F., Chou, C. Y., Chen, H. Y., Yeh, S. H., Chang, Y. C., & Jiang, J. A. 2017. On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Computers and Electronics in Agriculture, 136: 125-139.

  • Li, J., Danao, M. G. C., Chen, S.F., Li, S., Singh, V., & Brown, P. J. 2015. Prediction of the starch content and ethanol yields of 48 inbred varieties of sorghum grain using Near-Infrared (NIR) spectroscopy. Journal of Near Infrared Spectroscopy, 23(2): 85-92.

  • Chen, S.F., & Danao, M. G. C. 2015. Modeling the equilibrium moisture content (EMC) of miscanthus, miscane, energy cane, and energy sorghum. Fuel, 147: 18-26.

  • Chen, S.F., Danao, M. G. C., & Brown, P. J. 2015. Stalk strength and sugar content of 55 dual-purpose sorghum lines. Applied Engineering in Agriculture, 31(3): 489-496.

  • Danao, M. G. C., Chen, S.F., & Gates, R. S. 2014. Uncertainty estimation of ethanol concentration in simulated breath using enzyme-based biosensors. Accreditation and Quality Assurance, 19: 415-422.

  • Chen, S.F., Danao, M. G. C., Singh, V., & Brown, P. J. 2014. Determining sucrose and glucose levels in dual-purpose sorghum stalks by Fourier Transform Near-Infrared (FT-NIR) spectroscopy. Journal of the Science of Food and Agriculture, 94(12): 2569-2576.

  • Chen, S.F., & Danao, M. G. C. 2013. Decomposition and Solubility of H2O2: Implication in Exhaled Breath Condensate Sampling. Journal of Breath Research, 7(4): 046001 (9pp).

  • Chen, S.F., & Danao, M. G. C. 2013. Predictive models of ethanol concentrations in simulated exhaled breath and exhaled breath condensate under varied sampling conditions. Journal of Biomedical Science and Engineering, 6(8): 788-795.

Conference Papers

  • Lee, S. Y., Wang, J. C., Guo, M. C., Jiang, J. A., Hsieh, M. H., Peng, J. C., & Chen, S. F. 2022. Developing a Self-Guided Field Robot for Greenhouse Asparagus Monitoring. 2022 ASABE Annual International Meeting. American Society of Agricultural and Biological Engineers.

  • Hsueh, M. C., Dai, Y. L., Ling, C. P., Huang, J. H., Kuo, Y. F., & Chen, S. F. 2022. Developing Cucumber Foliar Disease Complex Identification Using One-hot and Multi-hot Labeling Methods. 2022 ASABE Annual International Meeting . American Society of Agricultural and Biological Engineers.

  • Hsiung, H. F., Lee, S. Y., Wang, J. C., Jiang, J. A., Liu, L. Y., Hsieh, M. H., & Chen, S.F. 2021. Application of mask region-based convolutional neural network on asparagus growth identification. ASABE Annual International Meeting, Virtual and On-Demand.

  • Lai, H. H., Chang, Y. T., Yang, J. I., & Chen, S.F. 2021. Application of convolutional neural networks on the development of plant-parasitic nematode image identification system. ASABE Annual International Meeting, Virtual and On-Demand.

  • Chen, X. M., Lin, C. C., Lin, S. R., & Chen, S.F. 2021. Application of region-based convolution neural network on tea diseases and harming insects identification. ASABE Annual International Meeting, Virtual and On-Demand.

  • Yu, T. K., Chang, Y. T., Hung, S. P., Lu, J. M., Peng, J. H., & Chen, S.F. 2021. Development of convolutional neural network based models for the prediction of specialty coffee aroma using gas chromatography-mass spectrometry. ASABE Annual International Meeting, Virtual and On-Demand.

  • Chang, Y. T., Hung, S. P., Lu, J. M., Peng, J. H., & Chen, S. F. 2019. Coffee flavor prediction: using deep learning methods on near-infrared spectroscopy (NIRS). 2019 ASABE Annual International Meeting. Boston, MA, USA.

  • Lin, Y. K., & Chen, S. F. 2019. Development of navigation system for tea field machine using semantic segmentation. AgriControl 2019: The 6th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture. Sydney, Australia.

  • Lee, S. H., Wu, C. C., & Chen, S. F. 2018. Development of image recognition and classification algorithm for tea leaf diseases using convolutional neural network. 2018 ASABE Annual International Meeting. Detroit, MI, USA.

  • Chen, Y. T., Wu, C. C., & Chen, S. F. 2018. Application of deep learning algorithm on tea shoot identification and localization. 2018 ASABE Annual International Meeting. Detroit, MI, USA.

  • Lin, Y. Z., & Chen, S. F. 2018. Immature fruit recognition using exposure fusion and machine learning. Proc. of the 9th Int. Symp. on Mach. and Mech. for Agri. and Biosys. Engr. Jeju, Korea.

  • Liao, Y. W., & Chen, S. F. 2017. Discriminant analysis of the geographical origins of Oolong tea using surface-enhanced Raman spectroscopy. 2017 ASABE Annual International Meeting, Spokane, WA, USA.

  • Chen, S. F., Cheng, B. C., Chan, Y. C., Wu, H., Xu, H., Chu, C. C., Li, Y. R., Hsiao, M., & Tsai, D. P. 2015. Surface plasmon resonance on optical discs for antibacterial application. 2015 International Symposium on Optical Memory, Toyama, Japan.

  • Kalita, P. K., Kumar, D. K., & Chen, S.F., 2015. Critical factors in the value chain responsible for postharvest losses in wheat and rice in developing countries. ASABE Annual International Meeting, New Orleans, LA, USA.

  • Li, J., Chen, S.F., Li, S., Singh, V., Brown, P. J., & Danao, M. G. C. 2014. Prediction of the starch content and ethanol yields of 44 inbred varieties of sorghum grain using Near-Infrared (NIR) spectroscopy. ASABE Annual International Meeting, Montreal, QC, Canada.

  • Sood, K., Denny, S., Sun, Y., Chen, S.F., & Danao, M. G. C. 2014. Variations in moisture content and composition of stored Miscanthus x giganteus. ASABE Annual International Meeting, Montreal, QC, Canada.

  • Chen, S.F., Brown, P. J., & Danao, M. G. C. 2013. Stalk strength and sugar content of different dual-purpose sorghum lines. ASABE Annual International Meeting, Kansas City, MI, USA.

  • Chen, S.F., & Danao, M. G. C. 2010. Modeling the effects of exhaled breath condensate collection conditions on biomarker concentrations. ASABE Annual International Meeting, Pittsburgh, PA, USA.

bottom of page