| A target detection model based on improved tiny-yolov3 under the environment of mining truck D Xiao, F Shan, Z Li, BT Le, X Liu, X Li IEEE Access 7, 123757-123764, 2019 | 70 | 2019 |
| Application of deep learning and near infrared spectroscopy in cereal analysis BT Le Vibrational Spectroscopy 106, 103009, 2020 | 60 | 2020 |
| Coal analysis based on visible-infrared spectroscopy and a deep neural network BT Le, D Xiao, Y Mao, D He Infrared Physics & Technology 93, 34-40, 2018 | 41 | 2018 |
| Coal mine area monitoring method by machine learning and multispectral remote sensing images D He, BT Le, D Xiao, Y Mao, F Shan, TTL Ha Infrared Physics & Technology 103, 103070, 2019 | 34 | 2019 |
| Coal classification method based on visible-infrared spectroscopy and an improved multilayer extreme learning machine Y Mao, BT Le, D Xiao, D He, C Liu, L Jiang, Z Yu, F Yang, X Liu Optics & Laser Technology 114, 10-15, 2019 | 31 | 2019 |
| Iron ore identification method using reflectance spectrometer and a deep neural network framework D Xiao, BT Le, TTL Ha Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 248, 119168, 2021 | 27 | 2021 |
| Detection method of TFe content of iron ore based on visible-infrared spectroscopy and IPSO-TELM neural network D Xiao, C Liu, BT Le Infrared Physics & Technology 97, 341-348, 2019 | 23 | 2019 |
| Salt content in saline-alkali soil detection using visible-near infrared spectroscopy and a 2D deep learning D Xiao, QH Vu, BT Le Microchemical Journal 165, 106182, 2021 | 22 | 2021 |
| An ore image segmentation method based on RDU-Net model D Xiao, X Liu, BT Le, Z Ji, X Sun Sensors 20 (17), 4979, 2020 | 22 | 2020 |
| Coal quality exploration technology based on an incremental multilayer extreme learning machine and remote sensing images BT Le, D Xiao, Y Mao, D He, J Xu, L Song IEEE Transactions on Geoscience and Remote Sensing 57 (7), 4192-4201, 2019 | 22 | 2019 |
| Rolling force prediction of hot rolling based on GA-MELM J Liu, X Liu, BT Le | 22* | |
| Rapid analysis of coal characteristics based on deep learning and visible-infrared spectroscopy D Xiao, BT Le Microchemical Journal 157, 104880, 2020 | 21 | 2020 |
| Coal exploration technology based on visible-infrared spectra and remote sensing data BT Le, D Xiao, D Okello, D He, J Xu, TT Doan Spectroscopy Letters 50 (8), 440-450, 2017 | 21 | 2017 |
| Coal classification based on visible, near-infrared spectroscopy and CNN-ELM algorithm LEB Tuan, X Dong, M Ya-chun, S Liang, H Da-kuo, L Shan-jun Spectroscopy and Spectral Analysis 38 (7), 2107-2112, 2018 | 19 | 2018 |
| Hyperspectral image classification based on average spectral-spatial features and improved hierarchical-ELM BT Le, TTL Ha Infrared Physics & Technology 102, 103013, 2019 | 17 | 2019 |
| Coal exploration based on a multilayer extreme learning machine and satellite images BT Le, D Xiao, Y Mao, D He, S Zhang, X Sun, X Liu IEEE Access 6, 44328-44339, 2018 | 14 | 2018 |
| Research on coal exploration technology based on satellite remote sensing D Xiao, BT Le, Y Mao, J Jiang, L Song, S Liu Journal of Sensors 2016, 2016 | 13 | 2016 |
| Research in magnesite grade classification based on near infrared spectroscopy and ELM algorithm YC Mao, D Xiao, JF Cheng, JH Jiang, T Ba, SJ Liu Guang pu xue yu guang pu fen xi= Guang pu 37 (1), 89-94, 2017 | 12 | 2017 |
| Coal identification based on a deep network and reflectance spectroscopy D Xiao, TTG Le, TT Doan, BT Le Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 270, 120859, 2022 | 11 | 2022 |
| Random search enhancement of incremental regularized multiple hidden layers ELM J Liu, X Liu, C Liu, BT Le, D Xiao IEEE Access 7, 36866-36878, 2019 | 9 | 2019 |
