Michael Lindenbaum

5.0k citations
93 papers · 3.0k indexed · h-index 27

Impact in

Papers in

Michael Lindenbaum

89 papers receiving 2.9k citations

Peers

Michael Lindenbaum
Comparison fields: 5 of 137
  • Computer Vision and Pattern Recognition 1.9k
  • Computer Graphics and Computer-Aided Design 257
  • Geology 218
  • Computational Mathematics 18
  • Media Technology 262
Replace Sameer Agarwal with:
Sameer Agarwal United States
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Alex Bronstein Israel
Iddo Drori United States
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Michael Werman Israel
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Citations per field
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Citations per year

Countries citing papers authored by Michael Lindenbaum

Since Specialization
Citations

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

Fields of papers citing papers by Michael Lindenbaum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Lindenbaum. 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 Lindenbaum. The network helps show where Michael Lindenbaum may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Michael Lindenbaum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Lindenbaum Line = papers co-authored together Michael Lindenbaum links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20240
4 201831
5
q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions
201313
6
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data
20129
7 200992
8 200843
9 20087
10 200618
11 20022
12 2000256
13 200044
14
Selective sampling for nearest neighbor classifiers
199912
15 199745
16 1997403
17 1996117
18
Applying VC-dimension analysis to 3D object recognition from perspective projections
19942
19 1994153
20 199310

About Michael Lindenbaum

Michael Lindenbaum is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Media Technology, Aerospace Engineering and Artificial Intelligence, having authored 93 papers that have together received 3.0k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (21 papers), Image and Object Detection Techniques (19 papers), Robotics and Sensor-Based Localization (17 papers), Medical Image Segmentation Techniques (16 papers), Advanced Image and Video Retrieval Techniques (13 papers), Machine Learning and Algorithms (11 papers), Digital Image Processing Techniques (11 papers) and Video Surveillance and Tracking Methods (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.9k citations), Computer Graphics and Computer-Aided Design (257 citations), Geology (218 citations), Computational Mathematics (18 citations) and Media Technology (262 citations). Michael Lindenbaum has collaborated with scholars based in Israel, United States and Japan. Frequent co-authors include Alfred M. Bruckstein⋆, Allan I. Levey, Moshe Porat, Israel A. Wagner, Y.Y. Zeevi, Ido Leichter, Roman Sandler, Tamar Avraham, Craig Gotsman and Ehud Rivlin. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, IEEE Transactions on Image Processing, Pattern Recognition and Pattern Recognition Letters.

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.

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