Chunli Lv

69 total papers · 694 total citations
49 papers, 385 citations indexed

About

Chunli Lv is a scholar working on Plant Science, Artificial Intelligence and Information Systems. According to data from OpenAlex, Chunli Lv has authored 49 papers receiving a total of 385 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Plant Science, 14 papers in Artificial Intelligence and 11 papers in Information Systems. Recurrent topics in Chunli Lv's work include Smart Agriculture and AI (26 papers), Plant Disease Management Techniques (13 papers) and Spectroscopy and Chemometric Analyses (9 papers). Chunli Lv is often cited by papers focused on Smart Agriculture and AI (26 papers), Plant Disease Management Techniques (13 papers) and Spectroscopy and Chemometric Analyses (9 papers). Chunli Lv collaborates with scholars based in China, United Kingdom and Norway. Chunli Lv's co-authors include Yan Zhang, Shiyun Wa, Longxiang Zhang, Siyu Cheng, Chang Zhou, Bei Pei, Jingfu Wang, Yan Zhu, Yutong Liu and Junyu Zhou and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Frontiers in Plant Science.

In The Last Decade

Chunli Lv

39 papers receiving 371 citations

Hit Papers

TinySegformer: A lightwei... 2024 2026 2024 20 40 60

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Chunli Lv 220 71 58 49 38 49 385
Savita Kolhe 176 0.8× 97 1.4× 57 1.0× 38 0.8× 25 0.7× 20 367
Jennifer Eunice 225 1.0× 63 0.9× 90 1.6× 84 1.7× 47 1.2× 20 435
G. P. Saradhi Varma 95 0.4× 91 1.3× 37 0.6× 69 1.4× 54 1.4× 51 353
Venkatramaphanikumar Sistla 170 0.8× 121 1.7× 58 1.0× 40 0.8× 21 0.6× 33 435
Hamoud Alshammari 107 0.5× 97 1.4× 57 1.0× 48 1.0× 75 2.0× 27 378
David Camilo Corrales 154 0.7× 78 1.1× 24 0.4× 38 0.8× 20 0.5× 40 398
Asif Iqbal Khan 154 0.7× 63 0.9× 53 0.9× 27 0.6× 27 0.7× 22 405
Rab Nawaz Bashir 171 0.8× 52 0.7× 26 0.4× 35 0.7× 29 0.8× 29 363
Sameerchand Pudaruth 193 0.9× 51 0.7× 98 1.7× 29 0.6× 73 1.9× 57 431
Mbuyu Sumbwanyambe 213 1.0× 39 0.5× 103 1.8× 22 0.4× 24 0.6× 59 339

Countries citing papers authored by Chunli Lv

Since Specialization
Citations

This map shows the geographic impact of Chunli Lv'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 Chunli Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chunli Lv more than expected).

Fields of papers citing papers by Chunli Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chunli Lv. 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 Chunli Lv. The network helps show where Chunli Lv may publish in the future.

Co-authorship network of co-authors of Chunli Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Chunli Lv. A scholar is included among the top collaborators of Chunli Lv 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 Chunli Lv. Chunli Lv is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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