| Deep learning associated with laser-induced breakdown spectroscopy (LIBS) for the prediction of lead in soil Y Zhao, M Lamine Guindo, X Xu, M Sun, J Peng, F Liu, Y He Applied spectroscopy 73 (5), 565-573, 2019 | 53 | 2019 |
| Advancing precision agriculture: The potential of deep learning for cereal plant head detection A Sanaeifar, ML Guindo, A Bakhshipour, H Fazayeli, X Li, C Yang Computers and Electronics in Agriculture 209, 107875, 2023 | 37 | 2023 |
| Geographic origin discrimination of millet using Vis-NIR spectroscopy combined with machine learning techniques MH Kabir, ML Guindo, R Chen, F Liu Foods 10 (11), 2767, 2021 | 30 | 2021 |
| Detection of hate speech texts using machine learning algorithm MSA Sanoussi, C Xiaohua, GK Agordzo, ML Guindo, AMMA Al Omari, ... 2022 IEEE 12th Annual Computing and Communication Workshop and Conference …, 2022 | 22 | 2022 |
| Potential of Vis-NIR to measure heavy metals in different varieties of organic-fertilizers using Boruta and deep belief network ML Guindo, MH Kabir, R Chen, F Liu Ecotoxicology and Environmental Safety 228, 112996, 2021 | 22 | 2021 |
| Application of laser-induced breakdown spectroscopy and chemometrics for the quality evaluation of foods with medicinal properties: A review MH Kabir, ML Guindo, R Chen, A Sanaeifar, F Liu Foods 11 (14), 2051, 2022 | 16 | 2022 |
| Deep Learning Combined with Hyperspectral Imaging Technology for Variety Discrimination of Fritillaria thunbergii MH Kabir, ML Guindo, R Chen, F Liu, X Luo, W Kong Molecules 27 (18), 6042, 2022 | 13 | 2022 |
| Particle swarm optimization and multiple stacked generalizations to detect nitrogen and organic-matter in organic-fertilizer using Vis-NIR ML Guindo, MH Kabir, R Chen, F Liu Sensors 21 (14), 4882, 2021 | 13 | 2021 |
| Digital techniques and trends for seed phenotyping using optical sensors F Liu, R Yang, R Chen, ML Guindo, Y He, J Zhou, X Lu, M Chen, Y Yang, ... Journal of Advanced Research 63, 1-16, 2024 | 10 | 2024 |
| Confocal Raman microspectroscopy combined with spectral screening algorithms for quantitative analysis of starch in rice X Wei, F Li, AB Perumal, A Sanaeifar, ML Guindo, Y Shi, Y He, F Liu Food Hydrocolloids 141, 108737, 2023 | 8 | 2023 |
| Chemometric approach based on explainable AI for rapid assessment of macronutrients in different organic fertilizers using fusion spectra ML Guindo, MH Kabir, R Chen, J Huang, F Liu, X Li, H Fang Molecules 28 (2), 799, 2023 | 7 | 2023 |
| A novel raisin segmentation algorithm based on deep learning and morphological analysis Y Zhao, ML Guindo, X Xu, X Shi, M Sun, Y He Engenharia Agrícola 39, 639-648, 2019 | 7 | 2019 |
| Heavy Metal Detection in Fritillaria thunbergii Using Laser-Induced Breakdown Spectroscopy Coupled with Variable Selection Algorithm and Chemometrics MH Kabir, ML Guindo, R Chen, X Luo, W Kong, F Liu Foods 12 (6), 1125, 2023 | 2 | 2023 |
| 基于 LIBS 技术和卷积神经网络的土壤铅含量等级快速分类 孙淼， 庄振华， 仲海鹏， 赵芸 浙江科技学院学报 31 (5), 373-380, 2019 | | 2019 |
| Detection of Starch Content in Rice Using Reflection-Type Terahertz Spectroscopy and Spatially Localized Rapid Sample Preparation Combined with Cs-Svr X Wei, F Li, ML Guindo, F Liu, Y He Available at SSRN 4806904, 0 | | |
| Potential of Explainable AI in Chemical Analytics to Detect Macronutrients in Organic Fertilizer Using LIBS, Vis-NIR, and Fusion Spectra ML Guindo, MH Kabir, R Chen, J Huang, F Liu, X Li, H Fang Vis-NIR, and Fusion Spectra, 0 | | |