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.
Flowing ConvNets for Human Pose Estimation in Videos
2015309 citationsTomas Pfister, James Charles et al.profile →
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 James Charles'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 James Charles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Charles more than expected).
This network shows the impact of papers produced by James Charles. 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 James Charles. The network helps show where James Charles may publish in the future.
Co-authorship network of co-authors of James Charles
This figure shows the co-authorship network connecting the top 25 collaborators of James Charles.
A scholar is included among the top collaborators of James Charles 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 James Charles. James Charles is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Charles, James, G. Arul Freeda Vinodhini, & R. Nagarajan. (2021). An Efficient Feature Selection with Weighted Extreme Learning Machine for Water Quality Prediction and Classification Model. Annals of the Romanian Society for Cell Biology. 1969–1994.3 indexed citations
5.
Charles, James, G. Arul Freeda Vinodhini, & R. Nagarajan. (2020). Isolation Forest With Optimal Adaptive Neuro-Fuzzy Inference System Based Water Quality Prediction and Classification Model. SSRN Electronic Journal.1 indexed citations
Pfister, Tomas, James Charles, & Andrew Zisserman. (2015). Flowing ConvNets for Human Pose Estimation in Videos. 1913–1921.309 indexed citations breakdown →
Pfister, Tomas, James Charles, & Andrew Zisserman. (2013). Large-scale Learning of Sign Language by Watching TV (Using Co-occurrences).. British Machine Vision Conference.28 indexed citations
Jiang, Jianmin, James Charles, & Konstantinos Demestichas. (2011). Toward Cooperative and Intelligent Optimization of Travel Planning and Energy Saving for Drivers of Fully Electric Vehicles.1 indexed citations
14.
Jiang, Jianmin, James Charles, & Konstantinos Demestichas. (2011). ECOGEM: A European Framework-7 Project. IEEE Vehicular Technology Magazine. 6(3). 22–26.6 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.