Hand Gesture Recognition Using Frequency‐Modulated Continuous Wave Radar on Tactile Displays for the Visually Impaired

Hand Gesture Recognition In article number 2400663, Pegah Pezeshkpour and co-workers present a hand gesture recognition application using a radar sensor for Braille displays. The range-time and velocity-time maps were extracted from the raw data and were processed in the form of spectrogram images. Using support vector machines and convolutional neural network approaches, ten hand gestures were successfully classified with high detection accuracy.

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Publication Details

Journal
Advanced Intelligent Systems
Published
2025-02-01
DOI
https://doi.org/10.1002/aisy.202570009
Citations
1
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
1.94
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article

Hand Gesture Recognition Using Frequency‐Modulated Continuous Wave Radar on Tactile Displays for the Visually Impaired

Pegah Pezeshkpour, Ahmed Hamza, Bastian E. Rapp, Santosh Kumar Prabhulingaiah
1 citations
Advanced Intelligent Systems
Hand Gesture Recognition Systems
1.94
article

Hand Gesture Recognition Using Frequency‐Modulated Continuous Wave Radar on Tactile Displays for the Visually Impaired

Pegah Pezeshkpour, Ahmed Hamza, Bastian E. Rapp, Santosh Kumar Prabhulingaiah
article en
1 citations

Abstract

Hand Gesture Recognition In article number 2400663, Pegah Pezeshkpour and co-workers present a hand gesture recognition application using a radar sensor for Braille displays. The range-time and velocity-time maps were extracted from the raw data and were processed in the form of spectrogram images. Using support vector machines and convolutional neural network approaches, ten hand gestures were successfully classified with high detection accuracy.

Advanced Intelligent SystemsVol. 7(2)
University of Freiburg (DE)
Openalex Percentile: Top 19%
Hand Gesture Recognition Systems
1.94
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