Gregor Lenz

1.7k citations
13 papers · 420 · 1 hit paper · h-index 5

Impact in

Papers in

Gregor Lenz

13 papers receiving 415 citations

Gregor Lenz's Hit Papers

Training Spiking Neural Networks Using Lessons From Deep Learning 2023 · 344 citations
3440+1+2Years since publication100200300

Peers

Gregor Lenz
Comparison fields: 5 of 54
  • Cognitive Neuroscience 147
  • Electrical and Electronic Engineering 311
  • Cellular and Molecular Neuroscience 80
  • Artificial Intelligence 139
  • Hardware and Architecture 11
Replace Eric Hunsberger with:
Eric Hunsberger Canada
Cédric Meyer France
Corey Lammie Australia
Arfan Ghani United Kingdom
De Ma China
Yanqi Chen China
Amirreza Yousefzadeh Netherlands
Jianhao Ding China
Bijan Vosoughi Vahdat Iran
Kristofor D. Carlson United States
Gregor Lenz relative to Eric Hunsberger Canada Eric Hunsberger's profile →
Citations per field
00.5×5.4×
Eric Hunsberger · 1×
Citations per year

Countries citing papers authored by Gregor Lenz

Since Specialization
Citations

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

Fields of papers citing papers by Gregor Lenz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Gregor Lenz, 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 Gregor Lenz Line = papers co-authored together Gregor Lenz links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1
Training Spiking Neural Networks Using Lessons From Deep Learning
Hit paper breakdown →
2023344
2 202430
3 20229
4 20238
5 20206
6 20084
7 20224
8
Event-based Dynamic Face Detection and Tracking Based on Activity.
20184
9 20194
10
High Speed Event-based Face Detection and Tracking in the Blink of an Eye
20183
11 19852
12 20221
13 20141

About Gregor Lenz

Gregor Lenz is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction, having authored 13 papers that have together received 420 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Neural dynamics and brain function (4 papers), Ferroelectric and Negative Capacitance Devices (2 papers), EEG and Brain-Computer Interfaces (2 papers), Gaze Tracking and Assistive Technology (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Advanced Clustering Algorithms Research (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Cognitive Neuroscience (147 citations), Electrical and Electronic Engineering (311 citations), Cellular and Molecular Neuroscience (80 citations), Artificial Intelligence (139 citations) and Hardware and Architecture (11 citations). Gregor Lenz has collaborated with scholars based in France, Switzerland and Germany. Frequent co-authors include Jason K. Eshraghian, Mohammed Bennamoun, Girish Dwivedi, Emre Neftci, Wei Lü, Xinxin Wang, Doo Seok Jeong, Max Ward, Sadique Sheik and Ryad Benosman. Their work appears in journals such as Frontiers in Neuroscience, Ultraschall in der Medizin - European Journal of Ultrasound, Proceedings of the IEEE, Nature Communications and Studies in health technology and informatics.

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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