Andreas Humm

441 citations
16 papers · 141 · h-index 7

Impact in

Papers in

Andreas Humm

14 papers receiving 135 citations

Peers

Andreas Humm
Comparison fields: 5 of 25
  • Signal Processing 79
  • Computer Vision and Pattern Recognition 106
  • Information Systems 53
  • Artificial Intelligence 64
  • Human-Computer Interaction 9
Replace Shi-Yong Neo with:
Shi-Yong Neo Singapore
Paulo Villegas Spain
Yushuo Guan China
Fatiha Djebbar United Arab Emirates
Yen-Lu Chow United States
Cheng-Ta Huang Taiwan
Adrià Giménez Spain
Pierre-Michel Bousquet France
Uno Fang Australia
Jean-Marc Ogier France
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Citations per field
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Citations per year

Countries citing papers authored by Andreas Humm

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Humm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Andreas Humm, 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 Andreas Humm Line = papers co-authored together Andreas Humm links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
MYIDEA - MULTIMODAL BIOMETRICS DATABASE, DESCRIPTION OF ACQUISITION PROTOCOLS
200538
2 200822
3 200714
4 200613
5 200612
6 20068
7
Scenario and Survey of Combined Handwriting and Speech Modalities for User Authentication
20068
8 20075
9 20075
10
MyIdea - Sensors Specifications and Acquisition Protocol
20065
11 20075
12 20073
13 20091
14
A novel method to generate Brute-Force Signature Forgeries
20061
15 20221
16 20220

About Andreas Humm

Andreas Humm is a scholar working on Computer Vision and Pattern Recognition, Information Systems, Artificial Intelligence, Signal Processing and Statistical and Nonlinear Physics, having authored 16 papers that have together received 141 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (11 papers), User Authentication and Security Systems (6 papers), Speech Recognition and Synthesis (4 papers), Natural Language Processing Techniques (4 papers), Biometric Identification and Security (4 papers), Music and Audio Processing (3 papers), Image Processing and 3D Reconstruction (2 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Signal Processing (79 citations), Computer Vision and Pattern Recognition (106 citations), Information Systems (53 citations), Artificial Intelligence (64 citations) and Human-Computer Interaction (9 citations). Andreas Humm has collaborated with scholars based in Switzerland, Australia and United States. Frequent co-authors include Jean Hennebert, Rolf Ingold, Bruno Dumas, Florian Évéquoz, Dijana Petrovska‐Delacrétaz, Horst Bunke, M. Kraetzl, François Du Toit and Reinhard Zimmermann. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans, Lecture notes in computer science, Studies in computational intelligence, Mohr Siebeck eBooks and Proceedings of the International Conference on Document Analysis and Recognition.

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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