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Yeyin Shi
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2020 – today
- 2024
- [j18]Jiating Li
, Yufeng Ge, Laila A. Puntel, Derek M. Heeren
Integrating UAV hyperspectral data and radiative transfer model simulation to quantitatively estimate maize leaf and canopy nitrogen content. Int. J. Appl. Earth Obs. Geoinformation 129: 103817 (2024) - 2023
- [j17]Jiating Li
Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model. Comput. Electron. Agric. 206: 107669 (2023) - [j16]Weiyue Xu
A lightweight SSV2-YOLO based model for detection of sugarcane aphids in unstructured natural environments. Comput. Electron. Agric. 211: 107961 (2023) - 2022
- [j15]Tianyi Wang
GIS-based volunteer cotton habitat prediction and plant-level detection with UAV remote sensing. Comput. Electron. Agric. 193: 106629 (2022) - [c1]Chong Yu
Energy-Aware Device Scheduling for Joint Federated Learning in Edge-assisted Internet of Agriculture Things. WCNC 2022: 1140-1145 - 2021
- [j14]Aziza Alzadjali, Mohammed H. Alali, Arun Narenthiran Veeranampalayam Sivakumar, Jitender S. Deogun, Stephen Scott, James C. Schnable, Yeyin Shi
Maize Tassel Detection From UAV Imagery Using Deep Learning. Frontiers Robotics AI 8: 600410 (2021) - [j13]Lin Wang
Early Detection of Encroaching Woody Juniperus virginiana and Its Classification in Multi-Species Forest Using UAS Imagery and Semantic Segmentation Algorithms. Remote. Sens. 13(10): 1975 (2021) - [j12]Ana I. de Castro
UAVs for Vegetation Monitoring: Overview and Recent Scientific Contributions. Remote. Sens. 13(11): 2139 (2021) - 2020
- [j11]Jiating Li, Cody Oswald, George L. Graef, Yeyin Shi
Improving model robustness for soybean iron deficiency chlorosis rating by unsupervised pre-training on unmanned aircraft system derived images. Comput. Electron. Agric. 175: 105557 (2020) - [j10]Yan Pang
Improved crop row detection with deep neural network for early-season maize stand count in UAV imagery. Comput. Electron. Agric. 178: 105766 (2020) - [j9]Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li
Comparison of Object Detection and Patch-Based Classification Deep Learning Models on Mid- to Late-Season Weed Detection in UAV Imagery. Remote. Sens. 12(13): 2136 (2020)
2010 – 2019
- 2019
- [j8]Jiyu Li
Vertical distribution and vortex structure of rotor wind field under the influence of rice canopy. Comput. Electron. Agric. 159: 140-146 (2019) - 2018
- [j7]Dongmei Chen, Yeyin Shi
Mapping wheat rust based on high spatial resolution satellite imagery. Comput. Electron. Agric. 152: 109-116 (2018) - [j6]Xiaoyang Zhao, Jian Zhang
Registration for Optical Multimodal Remote Sensing Images Based on FAST Detection, Window Selection, and Histogram Specification. Remote. Sens. 10(5): 663 (2018) - [j5]Wenan Yuan
Wheat Height Estimation Using LiDAR in Comparison to Ultrasonic Sensor and UAS. Sensors 18(11): 3731 (2018) - 2017
- [j4]Jinzhu Lu, Reza Ehsani, Yeyin Shi, Jaafar Abdulridha, Ana I. de Castro, Yunjun Xu:
Field detection of anthracnose crown rot in strawberry using spectroscopy technology. Comput. Electron. Agric. 135: 289-299 (2017) - [j3]Jian Zhang
Crop Classification and LAI Estimation Using Original and Resolution-Reduced Images from Two Consumer-Grade Cameras. Remote. Sens. 9(10): 1054 (2017) - 2015
- [j2]Yeyin Shi
Improvement of a ground-LiDAR-based corn plant population and spacing measurement system. Comput. Electron. Agric. 112: 92-101 (2015) - 2014
- [j1]Lin Yuan, Jingcheng Zhang, Yeyin Shi
Damage Mapping of Powdery Mildew in Winter Wheat with High-Resolution Satellite Image. Remote. Sens. 6(5): 3611-3623 (2014)
Coauthor Index
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