Lingshun Kong is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Oncology.
According to data from OpenAlex, Lingshun Kong has authored 3 papers receiving a total of 273 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Vision and Pattern Recognition, 1 paper in Molecular Biology and 1 paper in Oncology. Recurrent topics in Lingshun Kong's work include Image and Signal Denoising Methods (2 papers), Advanced Image Processing Techniques (2 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (1 paper). Lingshun Kong is often cited by papers focused on Image and Signal Denoising Methods (2 papers), Advanced Image Processing Techniques (2 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (1 paper). Lingshun Kong collaborates with scholars based in China and United States. Lingshun Kong's co-authors include Mingqiang Li, Jinshan Pan, Jianjun Ge, Jiangxin Dong, Guideng Li, Xiaohong Chen, Jessica K. Wang, Guikai Wu, Weian Zhao and David Baltimore and has published in prestigious journals such as Lab on a Chip.
In The Last Decade
Lingshun Kong
3 papers
receiving
268 citations
Hit Papers
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.
Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring
2023140 citationsLingshun Kong, Jiangxin Dong et al.profile →
Citations per year, relative to Lingshun Kong Lingshun Kong (= 1×)
peers
Kunbo Zhang
Countries citing papers authored by Lingshun Kong
Since
Specialization
Citations
This map shows the geographic impact of Lingshun Kong'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 Lingshun Kong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingshun Kong more than expected).
This network shows the impact of papers produced by Lingshun Kong. 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 Lingshun Kong. The network helps show where Lingshun Kong may publish in the future.
Co-authorship network of co-authors of Lingshun Kong
This figure shows the co-authorship network connecting the top 25 collaborators of Lingshun Kong.
A scholar is included among the top collaborators of Lingshun Kong 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 Lingshun Kong. Lingshun Kong is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
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.