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Xiuliang Jin
Researcher at University of Avignon
Publications - 109
Citations - 3561
Xiuliang Jin is an academic researcher from University of Avignon. The author has contributed to research in topics: Biology & Computer science. The author has an hindex of 24, co-authored 75 publications receiving 1922 citations. Previous affiliations of Xiuliang Jin include Center for Information Technology & Chinese Academy of Sciences.
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Journal ArticleDOI
A review of data assimilation of remote sensing and crop models
TL;DR: In this article, a detailed overview of the latest developments and applications of crop models, remote sensing techniques, and data assimilation methods in the growth status monitoring and yield estimation of crops is presented.
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Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery.
TL;DR: In this article, a high resolution image taken from a UAV at very low altitude with application to high throughput phenotyping in field conditions was used to estimate wheat plant density at the emergence stage.
Journal ArticleDOI
Ear density estimation from high resolution RGB imagery using deep learning technique
Simon Madec,Xiuliang Jin,Hao Lu,Benoit de Solan,Shouyang Liu,Florent Duyme,Emmanuelle Heritier,Frédéric Baret +7 more
TL;DR: Investigation of the potential of convolutional neural networks to provide accurate ear density using nadir high spatial resolution RGB images showed high and similar heritability, demonstrating that ear density derived from high resolution RGB imagery could replace the traditional counting method.
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High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms
Xiuliang Jin,Pablo J. Zarco-Tejada,Urs Schmidhalter,Matthew P. Reynolds,Malcolm J. Hawkesford,Rajeev K. Varshney,Tao Yang,Chengwei Nie,Zhenhai Li,Bo Ming,Yonggui Xiao,Yongdun Xie,Shaokun Li +12 more
TL;DR: Crop yields need to be improved in a sustainable manner to meet the expected worldwide increase in population over the coming decades as well as the effects of anticipated climate change; in this regard, genomics-assisted breeding has become a popular approach to food security.
Journal ArticleDOI
Combined Multi-Temporal Optical and Radar Parameters for Estimating LAI and Biomass in Winter Wheat Using HJ and RADARSAR-2 Data
Xiuliang Jin,Guijun Yang,Xingang Xu,Hao Yang,Haikuan Feng,Zhenhai Li,Jiaxiao Shen,Yubin Lan,Chunjiang Zhao +8 more
TL;DR: The results indicated that the COSVI-RPPs can be used to robustly estimate LAI and biomass and may provide a guideline for improving the estimations of LAi and biomass of winter wheat using multisource remote sensing data.