Michael P. Eckert

649 citations
17 papers · 440 · h-index 7

Impact in

Papers in

Michael P. Eckert

15 papers receiving 401 citations

Peers

Michael P. Eckert
Comparison fields: 5 of 56
  • Computer Vision and Pattern Recognition 287
  • Media Technology 97
  • Cognitive Neuroscience 122
  • Computer Graphics and Computer-Aided Design 18
  • Atomic and Molecular Physics, and Optics 57
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Jonas Gårding Sweden
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Citations per field
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Citations per year

Countries citing papers authored by Michael P. Eckert

Since Specialization
Citations

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

Fields of papers citing papers by Michael P. Eckert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Michael P. Eckert, 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 P. Eckert Line = papers co-authored together Michael P. Eckert links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 1998241
2 199450
3
The significance of eye movements and image acceleration for coding television image sequences
199334
4 199333
5 199530
6 199217
7 19937
8 19976
9 20005
10 19994
11
New Approaches in Medical Image Analysis
19993
12 19953
13 19942
14 19972
15 19972
16 19901
17
Separability of spatiotemporal spectra of image sequences. Ph.D. Thesis
19920

About Michael P. Eckert

Michael P. Eckert is a scholar working on Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Biomedical Engineering, having authored 17 papers that have together received 440 indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Advanced Vision and Imaging (3 papers), Advanced X-ray and CT Imaging (3 papers), Image and Signal Denoising Methods (3 papers), Radiation Dose and Imaging (3 papers), Visual perception and processing mechanisms (3 papers) and Advanced Image Fusion Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (287 citations), Media Technology (97 citations), Cognitive Neuroscience (122 citations), Computer Graphics and Computer-Aided Design (18 citations) and Atomic and Molecular Physics, and Optics (57 citations). Michael P. Eckert has collaborated with scholars based in United States and Australia. Frequent co-authors include Andrew P. Bradley, Gershon Buchsbaum, Andrew B. Watson, Dev P. Chakraborty, Gregory A. Carter, Anthony Maeder, Donald McLean and Robert Heard. Their work appears in journals such as Journal of the Optical Society of America A, Medical Physics, Philosophical Transactions of the Royal Society B Biological Sciences, Signal Processing and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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