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.
AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Problem?
2021178 citationsJun Ma, Yao Zhang et al.IEEE Transactions on Pattern Analysis and Machine Intelligenceprofile →
Citations per year, relative to Xingle An Xingle An (= 1×)
peers
Amirali Molaei
Countries citing papers authored by Xingle An
Since
Specialization
Citations
This map shows the geographic impact of Xingle An'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 Xingle An with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xingle An more than expected).
This network shows the impact of papers produced by Xingle An. 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 Xingle An. The network helps show where Xingle An may publish in the future.
Co-authorship network of co-authors of Xingle An
This figure shows the co-authorship network connecting the top 25 collaborators of Xingle An.
A scholar is included among the top collaborators of Xingle An 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 Xingle An. Xingle An is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
3 of 3 papers shown
1.
Ma, Jun, Yao Zhang, Song Gu, et al.. (2021). AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Problem?. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(10). 6695–6714.178 indexed citations breakdown →
2.
Ma, Jun, Yixin Wang, Xingle An, et al.. (2020). Towards Efficient COVID-19 CT Annotation: A Benchmark for Lung and Infection Segmentation. arXiv (Cornell University).51 indexed citations
3.
An, Xingle. (2007). Ear Recognition Based on Relation of Structure of Eyes, Mouth and Ear contour. Microcomputer Information.
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.