| Sorghum panicle detection and counting using unmanned aerial system images and deep learning Z Lin, W Guo Frontiers in Plant Science 11, 534853, 2020 | 70 | 2020 |
| Cotton stand counting from unmanned aerial system imagery using mobilenet and centernet deep learning models Z Lin, W Guo Remote Sensing 13 (14), 2822, 2021 | 41 | 2021 |
| Spatial-temporal multi-task learning for within-field cotton yield prediction LH Nguyen, J Zhu, Z Lin, H Du, Z Yang, W Guo, F Jin Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia …, 2019 | 35 | 2019 |
| Principles and applications of topography in precision agriculture AH Rabia, J Neupane, Z Lin, K Lewis, G Cao, W Guo Advances in agronomy 171, 143-189, 2022 | 31 | 2022 |
| Retrieving surface soil water content using a soil texture adjusted vegetation index and unmanned aerial system images H Gu, Z Lin, W Guo, S Deb Remote Sensing 13 (1), 145, 2021 | 22 | 2021 |
| Assessing fusarium oxysporum disease severity in cotton using unmanned aerial system images and a hybrid domain adaptation deep learning time series model A Abdalla, TA Wheeler, J Dever, Z Lin, J Arce, W Guo Biosystems Engineering 237, 220-231, 2024 | 10 | 2024 |
| Effects of irrigation rates on cotton yield as affected by soil physical properties and topography in the southern high plains J Neupane, W Guo, CP West, F Zhang, Z Lin Plos one 16 (10), e0258496, 2021 | 7 | 2021 |
| Field-scale spatial variability of soil calcium in a semi-arid region: Implications for soil erosion and site-specific management SUN Yazhou, GUO Wenxuan, DC Weindorf, SUN Fujun, DEB Sanjit, ... Pedosphere 31 (5), 705-714, 2021 | 7 | 2021 |
| Unmanned aerial systems and crop modeling for irrigation scheduling in the southern high plains Z Lin | 3 | 2019 |
| Assessing Spatial Pattern of Soil Microbial Community at Landscape Scale for Precision Soil Management J Neupane, W Guo, V Acosta-Martinez, F Zhang, Z Lin, A Cano ASA, CSSA and SSSA International Annual Meetings (2019), 2019 | 2 | 2019 |
| Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models (vol 13, 2822, 2021) Z Lin, W Guo REMOTE SENSING 14 (10), 2022 | | 2022 |
| Application of unmanned aerial systems and deep learning in high-throughput plant phenotyping Z Lin | | 2022 |
| Correction: Lin, Z.; Guo, W. Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models. Remote Sens. 2021, 13, 2822 Z Lin, W Guo Remote Sensing 14 (10), 2313, 2022 | | 2022 |
| Assessing Cotton Water Stress in Southern High Plains Using Unmanned Aerial Systems Y Sun, W Guo, X Yang, V Kovalskyy, Z Zhu, Z Lin, J Neupane ASA, CSSA and SSSA International Annual Meetings (2019), 2019 | | 2019 |
| Quantifying Cotton Water Stress Using Unmanned Aerial Systems Y Sun, W Guo, Z Zhu, X Yang, V Kovalskyy, Z Lin, Y Lin AGU Fall Meeting 2018, 2018 | | 2018 |
| Quantifying Cotton Water Stress Using Unmanned Aerial Systems V Kovalskyy, Y Sun, W Guo, Z Zhu, X Yang, Z Lin, Y Lin AGU Fall Meeting Abstracts 2018, B33F-2737, 2018 | | 2018 |
| Assessing within-Field Spatial Variability of Ca Using Proximal and Remote Sensing. Y Sun, W Guo, DC Weindorf, F Sun, SK Deb, Z Lin, J Neupane, A Raihan, ... ASA, CSSA, and CSA International Annual Meeting (2018), 2018 | | 2018 |
| Cotton Growth Variability in Relation to Topography and Soil Physical Properties in the High Plains. J Neupane, W Guo, A Raihan, Z Lin, JE Bennett, CP West ASA, CSSA and SSSA International Annual (2017), 2017 | | 2017 |
| Relationship between Microbial Community Composition, Soil Physicochemical Properties and Cotton Yields at a Field Scale. W Guo, V Acosta Martinez, A Cano, J Neupane, A Raihan, Z Lin ASA, CSSA and SSSA International Annual (2017), 2017 | | 2017 |
