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.
Individual recognition using gait energy image
20061.3k citationsBir Bhanu et al.IEEE Transactions on Pattern Analysis and Machine Intelligenceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Bir Bhanu'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 Bir Bhanu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bir Bhanu more than expected).
This network shows the impact of papers produced by Bir Bhanu. 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 Bir Bhanu. The network helps show where Bir Bhanu may publish in the future.
Co-authorship network of co-authors of Bir Bhanu
This figure shows the co-authorship network connecting the top 25 collaborators of Bir Bhanu.
A scholar is included among the top collaborators of Bir Bhanu 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 Bir Bhanu. Bir Bhanu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Weinberg, Brent D., et al.. (2020). Feature Disentanglement to Aid Imaging Biomarker Characterization for Genetic Mutations.. 349–364.1 indexed citations
Schmolze, Daniel, et al.. (2018). MVPNets: Multi-viewing Path Deep Learning Neural Networks for Magnification Invariant Diagnosis in Breast Cancer.. 189–194.1 indexed citations
Bhanu, Bir, et al.. (2012). Integrating crowd simulation for pedestrian tracking in a multi-camera system. 1–6.6 indexed citations
14.
An, Le, Mehran Kafai, & Bir Bhanu. (2012). Face recognition in multi-camera surveillance videos using Dynamic Bayesian Network. 1–6.9 indexed citations
Krawiec, Krzysztof & Bir Bhanu. (2003). Visual learning by evolutionary feature synthesis. International Conference on Machine Learning. 376–383.8 indexed citations
17.
Bhanu, Bir, et al.. (2002). Learning Composite Operators For Object Detection. Genetic and Evolutionary Computation Conference. 1003–1010.7 indexed citations
Henderson, Tom, Chuck Hansen, & Bir Bhanu. (1985). A framework for distributed sensing and control. International Joint Conference on Artificial Intelligence. 1106–1109.15 indexed citations
20.
Bhanu, Bir. (1983). Recognition of Occluded Objects.. International Joint Conference on Artificial Intelligence. 1136–1138.4 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.