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.
Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning
2019245 citationsGaowei Xu, Min Liu et al.Sensorsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Min Liu'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 Min Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min Liu more than expected).
This network shows the impact of papers produced by Min Liu. 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 Min Liu. The network helps show where Min Liu may publish in the future.
Co-authorship network of co-authors of Min Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Min Liu.
A scholar is included among the top collaborators of Min Liu 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 Min Liu. Min Liu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Liu, Min, et al.. (2021). Audio and Video Bimodal Emotion Recognition in Social Networks Based on Improved AlexNet Network and Attention Mechanism. Journal of Information Processing Systems. 17(4). 754–771.5 indexed citations
10.
Xu, Gaowei, et al.. (2019). Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning. Sensors. 19(5). 1088–1088.245 indexed citations breakdown →
Guo, Xiaobing & Min Liu. (2012). Cache-assign-forward architecture for efficient communication in hybrid delay-tolerant networks. China Communications. 9(6). 36–44.
14.
Liu, Min. (2010). Method to optimize Web service composition based on Bayes trust model. Computer Integrated Manufacturing Systems.3 indexed citations
15.
Liu, Min. (2010). Knowledge model for continuous casting equipment maintenance repair and overhaul. Computer Integrated Manufacturing Systems.1 indexed citations
16.
Liu, Min. (2010). Ontology mapping approach oriented to product information collaboration. Computer Integrated Manufacturing Systems.1 indexed citations
17.
Liu, Min. (2008). Evolution of Dalian tourism image. Journal of Dalian Maritime University.1 indexed citations
18.
Liu, Min. (2008). CPNs-based Validation Framework for Automatic Composition of Semantic Web Services. Jisuanji fangzhen.1 indexed citations
19.
Liu, Min. (2007). Verification mechanism for semantic Web service composition based on colored Petri-nets. Computer Integrated Manufacturing Systems.2 indexed citations
20.
Liu, Min. (2007). A Dynamic Service Combination Method Based on Agent.2 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.