Farong Xu

424 total citations · 1 hit paper
8 papers, 325 citations indexed

About

Farong Xu is a scholar working on Infectious Diseases, Animal Science and Zoology and Genetics. According to data from OpenAlex, Farong Xu has authored 8 papers receiving a total of 325 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Infectious Diseases, 4 papers in Animal Science and Zoology and 3 papers in Genetics. Recurrent topics in Farong Xu's work include Virus-based gene therapy research (3 papers), Helminth infection and control (2 papers) and Animal Virus Infections Studies (2 papers). Farong Xu is often cited by papers focused on Virus-based gene therapy research (3 papers), Helminth infection and control (2 papers) and Animal Virus Infections Studies (2 papers). Farong Xu collaborates with scholars based in China, Malaysia and United States. Farong Xu's co-authors include Yang Li, Mao Li, Xiangnan Liu, Guo Hui, Xinliang Tian, Kai Liu, Jiangtao Qi, Baoliang Pan, Ming Wang and Lei Zhou and has published in prestigious journals such as Virology, Computers and Electronics in Agriculture and Veterinary Microbiology.

In The Last Decade

Farong Xu

8 papers receiving 317 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

An improved YOLOv5 model based on visual attention mechanism: Application to recognition of tomato virus disease

2022 231 citations Jiangtao Qi, Xiangnan Liu et al. Computers and Electronics in Agriculture profile →

Peers

Farong Xu

PS

IS

PARAS

EEBS

CVPR

Jay Prakash Gupta India

Sachin Subedi United States

Ramesh Bahadur Bist United States

C. J. O’Neill Australia

Danilo Florentino Pereira Brazil

Andreas Baum Denmark

Mohammad Ashik Iqbal Khan Bangladesh

J.R.R. Dórea United States

Yuyan Liu China

Valeriy G. Narushin United Kingdom

Jay Prakash Gupta India

Farong Xu

160 ×1.0

PS

88 ×1.9

IS

115 ×2.7

PARAS

63 ×1.6

EEBS

69 ×1.9

CVPR

Citations per year, relative to Farong Xu Farong Xu (= 1×) peers Jay Prakash Gupta

Countries citing papers authored by Farong Xu

Since Specialization

Citations

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

Fields of papers citing papers by Farong Xu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Farong Xu

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Liu, Xiang, Meng Zhang, Yi Luo, et al.. (2025). Surface expression of PEDV nucleocapsid protein facilitates NK cell-mediated ADCC via anti-N nonneutralizing antibody. Veterinary Microbiology. 305. 110518–110518. 1 indexed citations

2.

Ni, Jie, et al.. (2025). Porcine respiratory coronavirus in 10 provinces of China: Molecular epidemiology, genetic diversity, and pathogenesis of the isolated PRCV/NM strain. Virology. 610. 110582–110582. 1 indexed citations

3.

Qi, Jiangtao, Xiangnan Liu, Kai Liu, et al.. (2022). An improved YOLOv5 model based on visual attention mechanism: Application to recognition of tomato virus disease. Computers and Electronics in Agriculture. 194. 106780–106780. 231 indexed citations breakdown →

4.

Alikhan, Mohammad Fathi, et al.. (2021). Evaluation of the National Tuberculosis Database System, “Tuberculosis Case Management (TBCM)”, for its Surveillance Function at Mae Sot Hospital, Thailand. 14(1). 20–26. 1 indexed citations

5.

Gao, Xiang, Dongliang Li, Jingyi Zhao, et al.. (2016). Complete Genome Sequence of Porcine Epidemic Diarrhea Virus from an Outbreak in a Vaccinated Farm in Shandong, China. Genome Announcements. 4(4). 7 indexed citations

6.

Xu, Farong, et al.. (2010). Survey of prevalence and control of ectoparasites in caged poultry in China. Veterinary Record. 167(24). 934–937. 54 indexed citations

7.

Xu, Farong, et al.. (2007). Pharmacokinetics of injectable long‐acting ivermectin aqueous suspension following subcutaneous administration in sheep. Journal of Veterinary Pharmacology and Therapeutics. 30(5). 486–488. 6 indexed citations

8.

Pan, Baoliang, et al.. (2006). Efficacy of an injectable formulation of eprinomectin against Psoroptes cuniculi, the ear mange mite in rabbits. Veterinary Parasitology. 137(3-4). 386–390. 24 indexed citations

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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