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.
Contour Detection and Hierarchical Image Segmentation
20103.5k citationsPablo Arbeláez, Michael Maire et al.profile →
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
2006786 citationsMichael Maire, Jitendra Malik et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Michael Maire'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 Michael Maire with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Maire more than expected).
This network shows the impact of papers produced by Michael Maire. 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 Michael Maire. The network helps show where Michael Maire may publish in the future.
Co-authorship network of co-authors of Michael Maire
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Maire.
A scholar is included among the top collaborators of Michael Maire 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 Michael Maire. Michael Maire is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Arbeláez, Pablo, Michael Maire, Charless C. Fowlkes, & Jitendra Malik. (2009). From contours to regions: An empirical evaluation. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2294–2301.292 indexed citations
Edwards, Jaety, et al.. (2004). Making Latin Manuscripts Searchable using gHMM's. UCL Discovery (University College London). 17. 385–392.44 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.