Thomas P. Vogl

2.1k total citations · 1 hit paper
38 papers, 1.4k citations indexed

About

Thomas P. Vogl is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Thomas P. Vogl has authored 38 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Cognitive Neuroscience and 8 papers in Electrical and Electronic Engineering. Recurrent topics in Thomas P. Vogl's work include Neural Networks and Applications (12 papers), Advanced Memory and Neural Computing (4 papers) and Neural dynamics and brain function (4 papers). Thomas P. Vogl is often cited by papers focused on Neural Networks and Applications (12 papers), Advanced Memory and Neural Computing (4 papers) and Neural dynamics and brain function (4 papers). Thomas P. Vogl collaborates with scholars based in United States, Germany and Romania. Thomas P. Vogl's co-authors include A. K. Rigler, Daniel L. Alkon, Nour-Eldin A. Nour-Eldin, Bita Panahi, Kim T. Blackwell, John M. Irvine, N Naguib, Renate Hammerstingl, Susan A. Werness and Wolfgang Hohenforst‐Schmidt and has published in prestigious journals such as Technometrics, Pattern Recognition and Review of Scientific Instruments.

In The Last Decade

Thomas P. Vogl

36 papers receiving 1.3k citations

Hit Papers

Accelerating the convergence of the back-propagation method 1988 2026 2000 2013 1988 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Accelerating the convergence of the back-propagation method
    1988 812 citations Thomas P. Vogl, A. K. Rigler et al. Biological Cybernetics profile →

Peers

Thomas P. Vogl
Hongjun Wang China
Marco Sciandrone Italy
Pai‐Hsuen Chen Taiwan
Kristiaan Pelckmans Sweden
Andrew R. Webb United Kingdom
Dat Nguyen United States
Yuemin Zhu France
Weixin Xie China
Jean‐Claude Nunes France
Dan Yamins United States
Hongjun Wang China
Thomas P. Vogl
Citations per year, relative to Thomas P. Vogl Thomas P. Vogl (= 1×) peers Hongjun Wang

Countries citing papers authored by Thomas P. Vogl

Since Specialization
Citations

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

Fields of papers citing papers by Thomas P. Vogl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas P. Vogl

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas P. Vogl. A scholar is included among the top collaborators of Thomas P. Vogl 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 Thomas P. Vogl. Thomas P. Vogl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kleemann, Johannes, Arjan Kuijper, Tobias Weberschock, et al.. (2018). Physical Attacks in Dermoscopy: An Evaluation of Robustness for clinical Deep-Learning. 4 indexed citations
2.
Vogl, Thomas P., Nour-Eldin A. Nour-Eldin, Renate Hammerstingl, Bita Panahi, & N Naguib. (2017). Microwave Ablation (MWA): Basics, Technique and Results in Primary and Metastatic Liver Neoplasms – Review Article. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 189(11). 1055–1066. 116 indexed citations
3.
Vogl, Thomas P., et al.. (2002). Classification of handwritten digits and Japanese Kanji. i. 97–102. 4 indexed citations
4.
Blackwell, Kim T., et al.. (1996). Orange juice classification with a biologically based neural network. Computers & Chemistry. 20(2). 261–266. 15 indexed citations
5.
Alkon, Daniel L., et al.. (1994). Biological plausibility of synaptic associative memory models. Neural Networks. 7(6-7). 1005–1017. 19 indexed citations
6.
Geist, Jon, R. A. Wilkinson, Stanley Janet, et al.. (1994). The Second Census Optical Character Recognition Systems Conference. 21 indexed citations
7.
Alkon, Daniel L., Kim T. Blackwell, Thomas P. Vogl, & Susan A. Werness. (1993). Biological plausibility of artificial neural networks: learning by non-Hebbian synapses. Oxford University Press eBooks. 31–49. 2 indexed citations
8.
Werness, Susan A., et al.. (1993). Associative learning in a network model of Hermissenda crassicornis. Biological Cybernetics. 69(1). 19–28. 10 indexed citations
9.
Werness, Susan A., et al.. (1992). Associative learning in a network model of Hermissenda crassicornis. Biological Cybernetics. 68(2). 125–133. 9 indexed citations
10.
Vogl, Thomas P., et al.. (1992). <title>Dynamically stable associative learning: a neurobiologically based ANN and its applications</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1710. 165–176. 2 indexed citations
11.
Alkon, Daniel L., et al.. (1990). Pattern-recognition by an artificial network derived from biologic neuronal systems. Biological Cybernetics. 62(5). 363–376. 36 indexed citations
12.
Voas, Robert B., et al.. (1990). Performance comparison of a neural network with human observers on a visual target detection task. Biological Cybernetics. 62(3). 185–191. 1 indexed citations
13.
Alkon, Daniel L., Francis Quek, & Thomas P. Vogl. (1988). Computer Modeling of Associative Learning. neural information processing systems. 1. 419–435. 5 indexed citations
14.
Vogl, Thomas P., et al.. (1988). Accelerating the convergence of the back-propagation method. Biological Cybernetics. 59(4-5). 257–263. 812 indexed citations breakdown →
15.
Vogl, Thomas P., et al.. (1971). Asymmetric Lens Design Using Bicubic Splines: Application to the Color TV Lighthouse. Applied Optics. 10(11). 2513–2513. 9 indexed citations
16.
Vogl, Thomas P., et al.. (1967). Semiautomatic Generation of Optical Prototypes. Applied Optics. 6(5). 969–969. 5 indexed citations
17.
Vogl, Thomas P., et al.. (1966). Recent advances in optimization techniques : proceedings. Wiley eBooks. 1 indexed citations
18.
Vogl, Thomas P., et al.. (1961). Photoconductive Time Constants and Related Characteristics of p-Type Gold-Doped Germanium. Journal of the Optical Society of America. 51(1). 70–70. 9 indexed citations
19.
Vogl, Thomas P., et al.. (1957). Method for the Generation of Very Fast Light Pulses. Review of Scientific Instruments. 28(10). 826–827. 15 indexed citations
20.
Vogl, Thomas P. & H. Evans. (1956). Electromagnetically Operated Ultra-High Vacuum Valve. Review of Scientific Instruments. 27(8). 657–657. 5 indexed citations

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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