Xin Sun

Orcid: 0000-0002-0658-7522

Affiliations:
  • North Dakota State University, Department of Agricultural and Biosystems Engineering, Fargo, ND, USA
  • Nanjing Agricultural University, Jiangsu, China (PhD 2013)


According to our database1, Xin Sun authored at least 11 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
An-augmenter: A unified platform for efficient image annotation and data augmentation.
SoftwareX, 2026

2025
Deep learning for plant stress detection: A comprehensive review of technologies, challenges, and future directions.
Comput. Electron. Agric., 2025

2024
Agricultural weed identification in images and videos by integrating optimized deep learning architecture on an edge computing technology.
Comput. Electron. Agric., January, 2024

A systematic review of hyperspectral imaging in precision agriculture: Analysis of its current state and future prospects.
Comput. Electron. Agric., 2024

WeedVision: A single-stage deep learning architecture to perform weed detection and segmentation using drone-acquired images.
Comput. Electron. Agric., 2024

2023
Palmer amaranth identification using hyperspectral imaging and machine learning technologies in soybean field.
Comput. Electron. Agric., December, 2023

Applications of deep learning in precision weed management: A review.
Comput. Electron. Agric., March, 2023

2021
UAV-Assisted Thermal Infrared and Multispectral Imaging of Weed Canopies for Glyphosate Resistance Detection.
Remote. Sens., 2021

A Technical Study on UAV Characteristics for Precision Agriculture Applications and Associated Practical Challenges.
Remote. Sens., 2021

Image based thermal sensing for glyphosate resistant weed identification in greenhouse conditions.
Comput. Electron. Agric., 2021

2019
Numerical simulation and field tests of minimum-tillage planter with straw smashing and strip laying based on EDEM software.
Comput. Electron. Agric., 2019


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