Sensor Signal Processing
Sensor Signal Processing is a methodological framework within the domain of robot sensors that transforms raw sensor data into refined, actionable information through computational algorithms, distinguishing it from other sensor-related processes by its focus on enhancing signal fidelity, extracting relevant features, and enabling accurate perception and decision-making in robotic systems.
507
Publications
25.7K
Citations
1.8K
Authors
613
Institutions
Publications per year
2017–2026
135
Variants
Sensor Signal Processing (Ssp)
507
A bioinspired flexible organic artificial afferent nerve
Yeongin Kim, Alex Chortos, Wentao Xu et al. · Science · 2018 · 1.4K citations
1–5 of 507
1.8K
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613
Georgia Institute of Technology
Atlanta, United States
10 h-index
35 publications
3.6K citations
Massachusetts Institute of Technology
Cambridge, United States
10 h-index
26 publications
5.5K citations

University of Naples Federico II
Naples, Italy
8 h-index
22 publications
810 citations
The University of Tokyo
Tokyo, Japan
7 h-index
20 publications
504 citations
University of Oxford
Oxford, United Kingdom
7 h-index
9 publications
393 citations
KU Leuven
Leuven, Belgium
6 h-index
15 publications
616 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
32 publications
1.8K citations

Imperial College London
London, United Kingdom
6 h-index
9 publications
820 citations
1–8 of 613
22 publications · 769 citations
17
h-index
24 publications · 654 citations
16
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15 publications · 702 citations
15
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10 publications · 528 citations
10
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9 publications · 254 citations
9
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1–5