Apr 18, 2022 · Gait recognition with wearable sensors is an effective approach to identifying people by recognizing their distinctive walking patterns.

Apr 29, 2022 · Gait recognition with wearable sensors is an effective approach to identifying people by recognizing their distinctive walking patterns.

Apr 27, 2022 · This study proposes an efficient network suitable for wearable devices without sacrificing prediction performance. We have modified the residual ...

Abstract: Gait recognition with wearable sensors is an effective approach to identifying people by recognizing their distinctive walking patterns. Deep learning ...

Gait recognition with wearable sensors is an effective approach to identifying people by recognizing their distinctive walking patterns. Deep learning-based ...

A hybrid deep neural network is proposed for robust gait feature representation, where features in the space and time domains are successively abstracted.

This work proposes to use multi-region size Convolutional Neural Network to recognize users from their gait patterns recorded from accelerometers and ...

A convolutional neural network model for gait identification in the sensor domain with multiple feature extraction blocks (MFEBP) is proposed

This study presents evidence toward understanding whether gait cycle events and biomechanical movements, usually considered in gait analysis, are helpful ...

Oct 1, 2021 · We have introduced a 3D convolutional neural network to extract robust and discriminative spatio-temporal features for gait recognition.