Max Mintz

28 papers receiving 481 citations

Peers

Max Mintz
Comparison fields: 5 of 47
  • Computer Vision and Pattern Recognition 110
  • Computational Theory and Mathematics 61
  • Artificial Intelligence 116
  • Control and Systems Engineering 81
  • Aerospace Engineering 64
Replace Jihun Ham with:
Jihun Ham United States
Wen Jiang China
Jinjie Huang China
Roberto Capobianco Italy
Amir Navot Israel
Xian Wei China
Robert Kaplow Canada
Mübeccel Demırekler Türkiye
Krzysztof Choromański United States
Hirotaka Hachiya Japan
Max Mintz relative to Jihun Ham United States Jihun Ham's profile →
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Citations per year

Countries citing papers authored by Max Mintz

Since Specialization
Citations

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

Fields of papers citing papers by Max Mintz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Max Mintz, 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 Max Mintz Line = papers co-authored together Max Mintz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001143
2 200470
3 201252
4 199150
5 198428
6
Active reduction of uncertainty in multisensor systems
198825
7 199620
8 197218
9 197314
10 198813
11 197810
12
Adaptive Image Segmentation
198810
13 19759
14 20049
15 19718
16 19728
17
A Stereo Confidence Metric Using Single View Imagery
20025
18 19724
19
Sensor modeling and robust sensor data fusion
19914
20
Sensor-Fusion With Statistical Decision Theory: A Prospectus of Research in the GRASP Lab
19903

About Max Mintz

Max Mintz is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Vision and Pattern Recognition, Control and Systems Engineering and Aerospace Engineering, having authored 32 papers that have together received 517 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (13 papers), Advanced Vision and Imaging (4 papers), Control Systems and Identification (3 papers), Probability and Statistical Research (3 papers), Statistical Distribution Estimation and Applications (3 papers), Guidance and Control Systems (3 papers), Stability and Control of Uncertain Systems (2 papers) and Teleoperation and Haptic Systems (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (110 citations), Computational Theory and Mathematics (61 citations), Artificial Intelligence (116 citations), Control and Systems Engineering (81 citations) and Aerospace Engineering (64 citations). Max Mintz has collaborated with scholars based in United States, Israel and Taiwan. Frequent co-authors include Gregory D. Hager, Geoffrey Egnal, Richard P. Wildes, Vijay Kumar, Tamer Başar, Jonathan Schug, Rajeev Alur, Franjo Ivančić, Calin A. Belta and Harvey N. Rubin. Their work appears in journals such as The Annals of Statistics, Expert Systems with Applications, Lecture notes in control and information sciences, Image and Vision Computing and The International Journal of Robotics Research.

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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