S. Knerr

1.5k citations
12 papers · 446 · h-index 9

Impact in

Papers in

S. Knerr

12 papers receiving 402 citations

Peers

S. Knerr
Comparison fields: 5 of 61
  • Computer Vision and Pattern Recognition 343
  • Human-Computer Interaction 63
  • Media Technology 81
  • Artificial Intelligence 239
  • Signal Processing 27
Replace R. Legault with:
R. Legault Canada
Li-Lun Wang United States
Kazuki Nakashima Japan
Huaigu Cao United States
Mou-Yen Chen United States
Fatoş T. Yarman-Vural Türkiye
Utpal Nandi India
Anjan Dutta Spain
Ihsin T. Phillips United States
Rongchun Zhao China
S. Knerr relative to R. Legault Canada R. Legault's profile →
Citations per field
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Citations per year

Countries citing papers authored by S. Knerr

Since Specialization
Citations

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

Fields of papers citing papers by S. Knerr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside S. Knerr, 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 S. Knerr Line = papers co-authored together S. Knerr links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 1999125
2 1992116
3
Pairwise Neural Network Classifiers with Probabilistic Outputs
199468
4 199832
5 200230
6
From Off-line to On-line Handwriting Recognition
200428
7 200517
8 200211
9 20099
10 19915
11 20023
12 20022

About S. Knerr

S. Knerr is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Media Technology and Signal Processing, having authored 12 papers that have together received 446 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (10 papers), Natural Language Processing Techniques (5 papers), Hand Gesture Recognition Systems (4 papers), Neural Networks and Applications (4 papers), Vehicle License Plate Recognition (3 papers), Image Processing and 3D Reconstruction (2 papers), Fuzzy Logic and Control Systems (2 papers) and Time Series Analysis and Forecasting (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (343 citations), Human-Computer Interaction (63 citations), Media Technology (81 citations), Artificial Intelligence (239 citations) and Signal Processing (27 citations). S. Knerr has collaborated with scholars based in France, Malaysia and Switzerland. Frequent co-authors include L. Personnaz, Gérard Dreyfus, Christian Viard-Gaudin, David J. Price, E. Augustin, Yong Haur Tay, Muhammad Irfan Khalid, Marcus Liwicki, James A. Pittman and Horst Bunke. Their work appears in journals such as Machine Vision and Applications, Computer Vision and Image Understanding, Pattern Recognition Letters, Data Archiving and Networked Services (DANS) and IEEE Transactions on Neural Networks.

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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