| Non-destructive and rapid evaluation of staple foods quality by using spectroscopic techniques: a review WH Su, HJ He, DW Sun Critical Reviews in Food Science and Nutrition 57 (5), 1039-1051, 2017 | 158 | 2017 |
| Fourier Transform Infrared and Raman and Hyperspectral Imaging Techniques for Quality Determinations of Powdery Foods: A Review WH Su, DW Sun Comprehensive Reviews in Food Science and Food Safety 17 (1), 104-122, 2018 | 154 | 2018 |
| Multispectral Imaging for Plant Food Quality Analysis and Visualization WH Su, DW Sun Comprehensive Reviews in Food Science and Food Safety 17 (1), 220-239, 2018 | 110 | 2018 |
| Evaluation of spectral imaging for inspection of adulterants in terms of common wheat flour, cassava flour and corn flour in organic Avatar wheat (Triticum spp.) flour WH Su, DW Sun Journal of Food Engineering 200, 59-69, 2017 | 99 | 2017 |
| Automatic Evaluation of Wheat Resistance to Fusarium Head Blight Using Dual Mask-RCNN Deep Learning Frameworks in Computer Vision WH Su, J Zhang, C Yang, R Page, T Szinyei, CD Hirsch, BJ Steffenson Remote Sensing 13 (1), 26, 2021 | 98 | 2021 |
| Advanced Machine Learning in Point Spectroscopy, RGB-and Hyperspectral-Imaging for Automatic Discriminations of Crops and Weeds: A review WH Su Smart Cities 3 (3), 767-792, 2020 | 84 | 2020 |
| Potential of hyperspectral imaging for visual authentication of sliced organic potatoes from potato and sweet potato tubers and rapid grading of the tubers according to … WH Su, DW Sun Computers and Electronics in Agriculture 125, 113-124, 2016 | 67 | 2016 |
| Facilitated wavelength selection and model development for rapid determination of the purity of organic spelt (Triticum spelta L.) flour using spectral imaging WH Su, DW Sun Talanta 155, 347-357, 2016 | 57 | 2016 |
| Mid-infrared (MIR) Spectroscopy for Quality Analysis of Liquid Foods WH Su, DW Sun Food Engineering Reviews 11 (3), 142-158, 2019 | 55 | 2019 |
| Variation analysis in spectral indices of volatile chlorpyrifos and non-volatile imidacloprid in jujube (Ziziphus jujuba Mill.) using near-infrared hyperspectral imaging (NIR … WH Su, DW Sun, JG He, LB Zhang Computers and Electronics in Agriculture 139, 41-55, 2017 | 55 | 2017 |
| Chemometrics in tandem with near infrared (NIR) hyperspectral imaging and Fourier transform mid infrared (FT-MIR) microspectroscopy for variety identification and cooking loss … WH Su, S Bakalis, DW Sun Biosystems Engineering 180, 70-86, 2019 | 48 | 2019 |
| Chemometric determination of time series moisture in both potato and sweet potato tubers during hot air and microwave drying using near/mid-infrared (NIR/MIR) hyperspectral … WH Su, S Bakalis, DW Sun Drying Technology 38 (5-6), 806-823, 2020 | 46 | 2020 |
| Hyperspectral imaging and improved feature variable selection for automated determination of deoxynivalenol in various genetic lines of barley kernels for resistance screening WH Su, C Yang, Y Dong, R Johnson, R Page, T Szinyei, CD Hirsch, ... Food Chemistry, 128507, 2021 | 44 | 2021 |
| Fourier transform mid-infrared-attenuated total reflectance (FTMIR-ATR) microspectroscopy for determining textural property of microwave baked tuber WH Su, S Bakalis, DW Sun Journal of Food Engineering 218, 1-13, 2018 | 43 | 2018 |
| Fluorescence imaging for rapid monitoring of translocation behaviour of systemic markers in snap beans for automated crop/weed discrimination WH Su, SA Fennimore, DC Slaughter Biosystems Engineering 186, 156-167, 2019 | 38 | 2019 |
| Comparative assessment of feature-wavelength eligibility for measurement of water binding capacity and specific gravity of tuber using diverse spectral indices stemmed from … WH Su, DW Sun Computers and Electronics in Agriculture 130, 69-82, 2016 | 37 | 2016 |
| Chemical imaging for measuring the time series variations of tuber dry matter and starch concentration WH Su, DW Sun Computers and Electronics in Agriculture 140, 361-373, 2017 | 36 | 2017 |
| Convolutional neural networks in computer vision for grain crop phenotyping: A review YH Wang, WH Su Agronomy 12 (11), 2659, 2022 | 35 | 2022 |
| Multivariate analysis of hyper/multi-spectra for determining volatile compounds and visualizing cooking degree during low-temperature baking of tubers WH Su, DW Sun Computers and Electronics in Agriculture 127, 561-571, 2016 | 35 | 2016 |
| SE-YOLOv5x: An optimized model based on transfer learning and visual attention mechanism for identifying and localizing weeds and vegetables JL Zhang, WH Su, HY Zhang, Y Peng Agronomy 12 (9), 2061, 2022 | 28 | 2022 |
Da-Wen SunMembers of Academia Europaea, Royal Irish Academy, Polish Academy of Sciences 孙大文：科学院院士Verified email at ucd.ie
