Ji Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Ji Li has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jun Qi
Department of Cardiothoracic Surgery, The People's Hospital of Changshou, Chongqing, 401220, China.
1 shared publication Lie Tang
1 shared publication- Lie Tang
Iowa State University
1 shared publication - Yueqin Wang
Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
1 shared publication
Latest Publications
- 2 October 2019
- Published by Springer Nature
- p. 755-763
Development of Single-Wavelength Integrating Nephelometer
- 2 October 2019
- Published by Springer Nature
- p. 755-763
Development of Single-Wavelength Integrating Nephelometer
- Open Access
- 1 December 2017
- Published by Elsevier in Computers and Electronics in Agriculture
- Vol. 143, 1-13
Developing a low-cost 3D plant morphological traits characterization system
- 1 December 2017
- Published by Elsevier in Computers and Electronics in Agriculture
- Vol. 143, 1-13
Open AccessDeveloping a low-cost 3D plant morphological traits characterization system
- 24 October 2017
- Published by Wiley in Journal of Field Robotics
- Vol. 35 (4) , 596-611
Crop recognition under weedy conditions based on 3D imaging for robotic weed control
A 3D time‐of‐flight camera was applied to develop a crop plant recognition system for broccoli and green bean plants under weedy conditions. The developed system overcame the previously unsolved problems caused by occluded canopy and illumination variation. An efficient noise filter was developed to remove the sparse noise points in 3D point cloud space. Both 2D and 3D features including the gradient of amplitude and depth image, surface curvature, amplitude percentile index, normal direction, and neighbor point count in 3D space were extracted and found effective for recognizing these two types of plants. Separate segmentation algorithms were developed for each of the broccoli and green bean plant in accordance with their 3D geometry and 2D amplitude characteristics. Under the experimental condition where the crops were heavily infested by various types of weed plants, detection rates over 88.3% and 91.2% were achieved for broccoli and green bean plant leaves, respectively. Additionally, the crop plants were segmented out with nearly complete shape. Moreover, the algorithms were computationally optimized, resulting in an image processing speed of over 30 frames per second.
- 24 October 2017
- Published by Wiley in Journal of Field Robotics
- Vol. 35 (4) , 596-611
Crop recognition under weedy conditions based on 3D imaging for robotic weed control
A 3D time‐of‐flight camera was applied to develop a crop plant recognition system for broccoli and green bean plants under weedy conditions. The developed system overcame the previously unsolved problems caused by occluded canopy and illumination variation. An efficient noise filter was developed to remove the sparse noise points in 3D point cloud space. Both 2D and 3D features including the gradient of amplitude and depth image, surface curvature, amplitude percentile index, normal direction, and neighbor point count in 3D space were extracted and found effective for recognizing these two types of plants. Separate segmentation algorithms were developed for each of the broccoli and green bean plant in accordance with their 3D geometry and 2D amplitude characteristics. Under the experimental condition where the crops were heavily infested by various types of weed plants, detection rates over 88.3% and 91.2% were achieved for broccoli and green bean plant leaves, respectively. Additionally, the crop plants were segmented out with nearly complete shape. Moreover, the algorithms were computationally optimized, resulting in an image processing speed of over 30 frames per second.