Performance Evaluation of Convolutional Neural Networks for Gait Recognition
Author:
Affiliation:
1. International Hellenic University, Greece
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3437120.3437276
Reference15 articles.
1. N. V. Boulgouris D. Hatzinakos and K.N. Plataniotis. 2005. Gait recognition: a challenging signal processing technology for biometric identification. IEEE signal processing magazine 22 6 78-90. N. V. Boulgouris D. Hatzinakos and K.N. Plataniotis. 2005. Gait recognition: a challenging signal processing technology for biometric identification. IEEE signal processing magazine 22 6 78-90.
2. J. C. Menant J. R. Steele H. B. Menz B. J. Munro and S. R. Lord. 2009. Effects of walking surfaces and footwear on temporo-spatial gait parameters in young and older people. Gait & posture 29 3 392-397. J. C. Menant J. R. Steele H. B. Menz B. J. Munro and S. R. Lord. 2009. Effects of walking surfaces and footwear on temporo-spatial gait parameters in young and older people. Gait & posture 29 3 392-397.
3. The influence of gait cadence on the ground reaction forces and plantar pressures during load carriage of young adults
4. Individual recognition using gait energy image
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