The Impact of Synthetic Data on Fall Detection Application
Date
2024-03
Authors
Ngu, Anne H. H.
Debnath, Minakshi
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Abstract
The accurate recognition of the dynamic of fall using deep learning requires a lot of data.
Three different methods for creating realistic synthetic fall data utilizing generative AI with diffusion, fall data extraction from 2D video recordings, and traditional data augmentation techniques are explored.
Description
Keywords
fall detection, synthetic data
Citation
Ngu, A. H. H., & Debnath, M. (2024). The impact of synthetic data on fall detection application. Poster presented at the Health Scholar Showcase, Translational Health Research Center, San Marcos, Texas.