代表性论文及科研项目:
[1]Dehua Gao,Lang Qiao,Di Song,Minzan Li,Hong Sun,Lulu An,Ruomei Zhao,Weijie TangandJinbo Qiao. 2022. In-field chlorophyll estimation based on hyperspectral images segmentation and pixel-wise spectra clustering of wheat canopy. Biosystems Engineering 217(41-55. 10.1016/j.biosystemseng.2022.03.003. (SCI: Q1,IF: 5.1,唯一第一作者)
[2]Dehua Gao,Lang Qiao,Lulu An,Hong Sun,MinZan Li,Ruomei Zhao,Weijie TangandDi Song. 2022. Diagnosis of maize chlorophyll content based on hybrid preprocessing and wavelengths optimization. Computers and Electronics in Agriculture 197(106934. 10.1016/j.compag.2022.106934. (SCI: Q1, IF: 8.3, top期刊,唯一第一作者)
[3]Dehua Gao,Lang Qiao,Lulu An,Ruomei Zhao,Hong Sun,Minzan Li,Weijie TangandNan Wang. 2022. Estimation of spectral responses and chlorophyll based on growth stage effects explored by machine learning methods. Crop Journal. 10.1016/j.cj.2022.07.011. (SCI: Q1, IF: 8.3, top期刊,IF: 6.6,中国科技期刊卓越行动计划'领军期刊',唯一第一作者)
[4]Dehua Gao,Minzan Li,Junyi Zhang,Di Song,Hong Sun,Lang QiaoandRuomei Zhao. 2021. Improvement of chlorophyll content estimation on maize leaf by vein removal in hyperspectral image. Computers and Electronics in Agriculture 184(106077. 10.1016/j.compag.2021.106077. (SCI: Q1, IF: 8.3, top期刊,唯一第一作者)
[5]Yang, S., et al., A grapevine trunks and intra-plant weeds segmentation method based on improved Deeplabv3 Plus. Computers and Electronics in Agriculture, 2024. 227: p. 109568. (SCI: Q1, IF: 8.3, top期刊, 通讯作者)
[6]Lang Qiao,Dehua Gao,Junyi Zhang,Minzan Li,Hong SunandJunyong Ma. 2020. Dynamic Influence Elimination and Chlorophyll Content Diagnosis of Maize Using UAV Spectral Imagery. Remote Sensing 12(16). 2650. 10.3390/rs12162650. (合作发表)
[7]Di Song,Dehua Gao,Hong Sun,Lang Qiao,Ruomei Zhao,Weijie TangandMinzan Li. 2021. Chlorophyll content estimation based on cascade spectral optimizations of interval and wavelength characteristics. Computers and Electronics in Agriculture 189(106413. 10.1016/j.compag.2021.106413. (SCI: Q1, IF: 8.3, top期刊,合作发表)
[8]Song, D., et al., Development of crop chlorophyll detector based on a type of interference filter optical sensor. Computers and Electronics in Agriculture, 2021. 187: p. 106260.(SCI: Q1, IF: 8.3, top期刊,合作发表)
[9]Liangliang Yang,Dehua Gao,Yohei Hoshino,Soichiro Suzuki,Ying CaoandShuming Yang. 2017. Evaluation of the accuracy of an auto-navigation system for a tractor in mountain areas. 133-138, 2017. (IEEE会议论文,合作发表)
[10]张俊逸,高德华,宋迪,乔浪,孙红,李民赞and李莉. 2022. PROSPECT模型的特征波长优化与作物叶绿素含量检测.光谱学与光谱分析42(05). 1514-1521. (合作发表)
[11]龙耀威,李民赞,高德华,张智勇,孙红andZhang Qin. 2020.基于作物谱图特征的植株分割与叶绿素分布检测.光谱学与光谱分析40(07). 2253-2258. (合作发表)
[12]Haojie Liu,Minzan Li,Junyi Zhang,Dehua Gao,Hong Sun,Man ZhangandJingzhu Wu. 2019. A novel wavelength selection strategy for chlorophyll prediction by MWPLS and GA. International Journal of Agricultural and Biological Engineering 12(5). 149-155. 10.25165/j.ijabe.20191205.4033. (SCI: Q2, 合作发表)
[13]Haojie Liu,Minzan Li,Junyi Zhang,Dehua Gao,Hong Sunand Liwei Yang. 2018. Estimation of chlorophyll content in maize canopy using wavelet denoising and SVR method. International Journal of Agricultural and Biological Engineering 11(6). 132-137. 10.25165/j.ijabe.20181106.3072. (SCI: Q2, 合作发表)
[14]Yang, S., et al., Parameter optimization for a scraping-rotating-brushing dehilling machine using EDEM. International Journal of Agricultural and Biological Engineering, 2024. 17(6): p. 152-165. (SCI: Q2, 合作发表)
[15]Zhang, J., et al., Detection of Canopy Chlorophyll Content of Corn Based on Continuous Wavelet Transform Analysis. Remote Sensing, 2020. 12(17): p. 2741. (SCI: Q2, 合作发表)
[16]Zhao, R., et al., Deep learning assisted continuous wavelet transform-based spectrogram for the detection of chlorophyll content in potato leaves. Computers and Electronics in Agriculture, 2022. 195: p. 106802. (SCI: Q1, IF: 8.3, top期刊,合作发表)
主编或参编的学术著作或教材:
《单片机原理及应用》(数字教材),西安交通大学出版社,2025 年 3 月 第 1 版,978-7-900975-73-7
专利及软件著作:
获实用新型专利7项,申请国家发明专利3项