Michael J. Klaiber
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence
- Co-authors
- Donald G. BaileySven SimonGhada DessoukyZhe WangWolfgang EckerTimo D. HämäläinenMuhammad ShafiqueHartmut Weule
- Topics
- Digital Image Processing Techniques (8 papers)CCD and CMOS Imaging Sensors (8 papers)Medical Image Segmentation Techniques (7 papers)
- Journals
- CIRP AnnalsIEEE Transactions on Circuits and Systems for Video TechnologyJournal of Mathematical Imaging and Vision
- Partner nations
- GermanyNew ZealandAustria
In The Last Decade
Michael J. Klaiber
15 papers receiving 124 citations
Peers
Comparison fields: 5 of 41
- Computer Vision and Pattern Recognition 79
- Electrical and Electronic Engineering 58
- Hardware and Architecture 23
- Computer Networks and Communications 21
- Artificial Intelligence 11
Countries citing papers authored by Michael J. Klaiber
This map shows the geographic impact of Michael J. Klaiber'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 J. Klaiber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael J. Klaiber more than expected).
Fields of papers citing papers by Michael J. Klaiber
This network shows the impact of papers produced by Michael J. Klaiber. 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 J. Klaiber. The network helps show where Michael J. Klaiber may publish in the future.
Co-authorship network of co-authors of Michael J. Klaiber
This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Klaiber. A scholar is included among the top collaborators of Michael J. Klaiber based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael J. Klaiber. Michael J. Klaiber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Automated HW/SW Co-design for Edge AI: State, Challenges and Steps Ahead: Special Session Paper | 0 |
| 2 | 1 | |
| 3 | 12 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | 9 | |
| 7 | 4 | |
| 8 | 26 | |
| 9 | 18 | |
| 10 | 4 | |
| 11 | 4 | |
| 12 | 15 | |
| 13 | Fast lossless image compression with 2D Golomb parameter adaptation based on JPEG-LS | 1 |
| 14 | 2 | |
| 15 | 0 | |
| 16 | 18 | |
| 17 | 1 |
About Michael J. Klaiber
Michael J. Klaiber is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Computer Graphics and Computer-Aided Design, having authored 17 papers that have together received 128 indexed citations. Recurring topics across this work include Digital Image Processing Techniques (8 papers), CCD and CMOS Imaging Sensors (8 papers) and Medical Image Segmentation Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (79 citations), Hardware and Architecture (23 citations) and Biophysics (6 citations). Michael J. Klaiber has collaborated with scholars based in Germany, New Zealand and Austria. Frequent co-authors include Donald G. Bailey, Sven Simon, Sven Simon, Ghada Dessouky, Zhe Wang, Wolfgang Ecker, Timo D. Hämäläinen, Muhammad Shafique, Hartmut Weule and Muhammad Abdullah Hanif. Their work appears in journals such as CIRP Annals, IEEE Transactions on Circuits and Systems for Video Technology and Journal of Mathematical Imaging and Vision.
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.