Non-local Image Dehazing

1.2k indexed citations
published 2016

Countries where authors are citing Non-local Image Dehazing

Specialization
Citations

This map shows the geographic impact of Non-local Image Dehazing. 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 Non-local Image Dehazing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Non-local Image Dehazing more than expected).

Fields of papers citing Non-local Image Dehazing

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Non-local Image Dehazing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Non-local Image Dehazing.

About Non-local Image Dehazing

This paper, published in 2016, received 1.2k indexed citations . Written by Dana Berman, Tali Treibitz and Shai Avidan covering the research area of Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (1.2k citations), Media Technology (667 citations), Safety, Risk, Reliability and Quality (136 citations), Biomedical Engineering (44 citations) and Computer Graphics and Computer-Aided Design (35 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.

This paper is also available at doi.org/10.1109/cvpr.2016.185.

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