Rainer Hoch
Impact in
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- Handwritten Text Recognition Techniques
- Image Retrieval and Classification Techniques
- Image Processing and 3D Reconstruction
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Papers in
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- Text and Document Classification Technologies 6
- Algorithms and Data Compression 6
- Natural Language Processing Techniques 5
- Semantic Web and Ontologies 4
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- Handwritten Text Recognition Techniques 7
- Image Retrieval and Classification Techniques 4
- Advanced Image and Video Retrieval Techniques 3
- Journals
- International Journal on Document Analysis and Recognition (IJDAR) (1 paper)Machine Vision and Applications (1 paper)Computer (1 paper)International Journal of Pattern Recognition and Artificial Intelligence (2 papers)International ACM SIGIR Conference on Research and Development in Information Retrieval (1 paper)
- Partner nations
- Germany
In The Last Decade
Rainer Hoch
15 papers receiving 254 citations
Peers
Comparison fields: 5 of 60
- Computer Vision and Pattern Recognition 119
- Hardware and Architecture 37
- Artificial Intelligence 127
- Information Systems 66
- Computer Networks and Communications 57
Countries citing papers authored by Rainer Hoch
This map shows the geographic impact of Rainer Hoch'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 Rainer Hoch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rainer Hoch more than expected).
Fields of papers citing papers by Rainer Hoch
This network shows the impact of papers produced by Rainer Hoch. 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 Rainer Hoch. The network helps show where Rainer Hoch may publish in the future.
Co-authorship network
The 5 scholars most cited alongside Rainer Hoch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 0 | |
| 2 | 2002 | 1 | |
| 3 | 2002 | 4 | |
| 4 | 2002 | 9 | |
| 5 | 1999 | 115 | |
| 6 | 1998 | 16 | |
| 7 | 1996 | 3 | |
| 8 | 1996 | 5 | |
| 9 | From paper to office document standard representation | 1995 | 1 |
| 10 | 1995 | 5 | |
| 11 | 1994 | 31 | |
| 12 | 1993 | 6 | |
| 13 | Hybrid Structured Dictionary for Improving Text Recognition. | 1992 | 4 |
| 14 | 1992 | 77 | |
| 15 | 1992 | 2 | |
| 16 | 1991 | 1 |
About Rainer Hoch
Rainer Hoch is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Information Systems and Management Information Systems, having authored 16 papers that have together received 280 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (7 papers), Text and Document Classification Technologies (6 papers), Algorithms and Data Compression (6 papers), Natural Language Processing Techniques (5 papers), Image Retrieval and Classification Techniques (4 papers), Semantic Web and Ontologies (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Mathematics, Computing, and Information Processing (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (119 citations), Hardware and Architecture (37 citations), Artificial Intelligence (127 citations), Information Systems (66 citations) and Computer Networks and Communications (57 citations). Rainer Hoch has collaborated with scholars based in Germany. Frequent co-authors include Andreas Dengel, Markus Junker, Thomas Kieninger, Norbert Kühn and S. Baumann. Their work appears in journals such as International Journal on Document Analysis and Recognition (IJDAR), Machine Vision and Applications, Computer, International Journal of Pattern Recognition and Artificial Intelligence and International ACM SIGIR Conference on Research and Development in Information Retrieval.
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.