Huiren Tian

643 citations
12 papers · 439 indexed · 1 hit paper · h-index 10
Topics
Remote Sensing in Agriculture (11 papers)Smart Agriculture and AI (7 papers)Greenhouse Technology and Climate Control (6 papers)

In The Last Decade

Huiren Tian

10 papers receiving 430 citations

Hit Papers

A deep learning framework combining CNN and GRU for impro...20232026202420252023255075

Peers

Huiren Tian
Comparison fields: 5 of 60
  • Ecology 244
  • Plant Science 227
  • Environmental Engineering 116
  • Global and Planetary Change 82
  • Atmospheric Science 60
Replace Tiecheng Bai with:
Tiecheng Bai China
Samuel Ihuoma Canada
Sumanta Das India
Abhishek Danodia India
Xun Yu China
Liangsheng Shi China
Wenxuan Guo United States
Zhanyu Dong China
Yi Bai China
Huiren Tian relative to Tiecheng Bai China Tiecheng Bai's profile →
Citations per field
00.5×1.5×1.8×
Tiecheng Bai · 1×
Citations per year

Countries citing papers authored by Huiren Tian

Since Specialization
Citations

This map shows the geographic impact of Huiren Tian's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Huiren Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huiren Tian more than expected).

Fields of papers citing papers by Huiren Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Huiren Tian. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Huiren Tian. The network helps show where Huiren Tian may publish in the future.

Co-authorship network of co-authors of Huiren Tian

This figure shows the co-authorship network connecting the top 25 collaborators of Huiren Tian. A scholar is included among the top collaborators of Huiren Tian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Huiren Tian. Huiren Tian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
1 0
2 0
3 10
4
A deep learning framework combining CNN and GRU for improving wheat yield estimates using time series remotely sensed multi-variablesbreakdown →
77
5 11
6 123
7 27
8 72
9 12
10 34
11 55
12 18

About Huiren Tian

Huiren Tian is a scholar working on Ecology, Plant Science and Environmental Engineering, having authored 12 papers that have together received 439 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (11 papers), Smart Agriculture and AI (7 papers) and Greenhouse Technology and Climate Control (6 papers). The work is most often cited by research in Ecology (244 citations), Environmental Engineering (116 citations) and Plant Science (227 citations). Huiren Tian has collaborated with scholars based in China, United Kingdom and Belgium. Frequent co-authors include Pengxin Wang, Kevin Tansey, Shuyu Zhang, Jingqi Zhang, Hongmei Li, Dong Han, Wenting Quan, Junming Liu, Jie Wang and Hongmei Li. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Agricultural and Forest Meteorology and Computers and Electronics in Agriculture.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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