The F-GCN significantly enhances feature extraction in gait analysis by capturing temporal dependencies within the gait cycle using frequency domain principles.
May 23, 2024 · In summary, our innovative FP-GCN contributes to advancing feature extraction and pathological gait recognition, which may offer potential ...
Jun 21, 2024 · In summary, our innovative FP-GCN contributes to advancing feature extraction and pathological gait recognition, which may offer potential ...
In this paper, we propose a Frequency Pyramid Graph Convolutional Network (FP-GCN), advocating to complement temporal analysis and further enhance spatial ...
In this paper, we propose a Frequency Pyramid Graph Convolutional Network (FP-GCN), advocating to complement temporal analysis and further enhance spatial ...
Figure 4 depicts the F-GCN model, highlighting its ability to minimize the noise introduced by human skeleton prediction algorithms and to capture the intrinsic ...
FP-GCN: Frequency Pyramid Graph Convolutional Network for Enhancing Pathological Gait Classification. Sensors 2024, 24, 3352. https://doi.org/10.3390 ...
Inspired by the frequency-based video processing mechanism of human visual system, a video-based SlowFast GCN network is proposed to quantify the gait ...
This study investigated a spatiotemporal graph convolutional network model (ST-GCN), using attention techniques applied to pathological-gait classification from ...
The temporal-tightly graph convolutional network (TT-GCN) is proposed to extract temporal features to obtain tight temporal dependencies and enhance the ...