M.T. Eismann

700 citations
12 papers · 554 indexed · h-index 7

Impact in

Papers in

M.T. Eismann

11 papers receiving 519 citations

Peers

M.T. Eismann
Comparison fields: 5 of 40
  • Media Technology 509
  • Computer Vision and Pattern Recognition 292
  • Atmospheric Science 93
  • Computational Mathematics 2
  • Ecology 65
Replace Zhijun Wang with:
Zhijun Wang China
Todd Wittman United States
Chiru Ge China
Luca Capobianco Italy
Claire Thomas France
Laëtitia Loncan France
Xiaobing Dai China
William S. Hungate United States
Ingebjørg Kåsen Norway
Marcus Borengasser United States
M.T. Eismann relative to Zhijun Wang China Zhijun Wang's profile →
Citations per field
00.5×1.5×2.4×
Zhijun Wang · 1×
Citations per year

Countries citing papers authored by M.T. Eismann

Since Specialization
Citations

This map shows the geographic impact of M.T. Eismann'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 M.T. Eismann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.T. Eismann more than expected).

Fields of papers citing papers by M.T. Eismann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.T. Eismann. 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 M.T. Eismann. The network helps show where M.T. Eismann may publish in the future.

Co-authors

The 17 scholars most cited alongside M.T. Eismann, 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 M.T. Eismann Line = papers co-authored together M.T. Eismann links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2004211
2 2005140
3 2004117
4 201139
5 200616
6 200414
7 19896
8 20026
9 19882
10
Utility Analysis of High-Resolution Multispectral Imagery. Volume 4. Image Based Sensor Model (IBSM) Version 2.0 Technical Description.
19962
11 20081
12 20050

About M.T. Eismann

M.T. Eismann is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics, Aerospace Engineering and Ecology, having authored 12 papers that have together received 554 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (6 papers), Advanced Image Fusion Techniques (4 papers), Image and Signal Denoising Methods (3 papers), Infrared Target Detection Methodologies (3 papers), Optical and Acousto-Optic Technologies (2 papers), Remote Sensing in Agriculture (2 papers), Calibration and Measurement Techniques (2 papers) and Adaptive optics and wavefront sensing (2 papers). The work is most often cited by research in Media Technology (509 citations), Computer Vision and Pattern Recognition (292 citations), Atmospheric Science (93 citations), Computational Mathematics (2 citations) and Ecology (65 citations). M.T. Eismann has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Russell C. Hardie, Roger Hardie, Gary Wilson, Joshua N. Ash, Randolph L. Moses, Anthony M. Tai, Jack N. Cederquist, Paul McManamon, Edward Watson and P. J. S. Watson. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing, Zenodo (CERN European Organization for Nuclear Research) and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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