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.
BLIND CONTRAST ENHANCEMENT ASSESSMENT BY GRADIENT RATIOING AT VISIBLE EDGES
2011585 citationsNicolas Hautière, Jean‐Philippe Tarel 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 Didier Aubert'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 Didier Aubert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Didier Aubert more than expected).
This network shows the impact of papers produced by Didier Aubert. 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 Didier Aubert. The network helps show where Didier Aubert may publish in the future.
Co-authorship network of co-authors of Didier Aubert
This figure shows the co-authorship network connecting the top 25 collaborators of Didier Aubert.
A scholar is included among the top collaborators of Didier Aubert 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 Didier Aubert. Didier Aubert is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Aubert, Didier, et al.. (2006). Mesure du contraste local dans les images, application à la mesure de distance de visibilité par caméra embarquée. Traitement du signal. 23(2). 145–158.2 indexed citations
11.
Hautière, Nicolas, Raphaël Labayrade, & Didier Aubert. (2006). Estimation of the Visibility Distance by Stereovision : A Generic Approach(Intelligent Transport Systems, Machine Vision Applications). IEICE Transactions on Information and Systems. 89(7). 2084–2091.4 indexed citations
Hautière, Nicolas, Didier Aubert, & Michel Jourlin. (2006). Mesure du contraste local dans les images, Application à la mesure de distance de visibilité par caméra embarquée Measurement of local contrast in images, Application to the measurement of visibility distance through use of an onboard camera.6 indexed citations
14.
Aubert, Didier. (2005). Lewis Hine et les images anonymes du Pittsburgh Survey. SHILAP Revista de lepidopterología.1 indexed citations
Labayrade, Raphaël & Didier Aubert. (2004). Robust and Fast Stereovision Based Obstacles Detection for Driving Safety Assistance. IEICE Transactions on Information and Systems. 87(1). 80–88.11 indexed citations
17.
Labayrade, Raphaël, et al.. (2003). ONBOARD ROAD OBSTACLES DETECTION IN NIGHT CONDITION USING BINOCULAR CCD CAMERAS. 2003.6 indexed citations
Labayrade, Raphaël & Didier Aubert. (2002). Robust and Fast Stereovision Based Road Obstacles Detection for Driving Safety Assistance.. Machine Vision and Applications. 624–627.19 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.