Scaling Human Activity Recognition via Deep Learning-based Domain Adaptation

138 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Human Activity Recognition With Smartphone and Wearable Sensors Using Deep Learning Techniques: A Review (2021, background): “• Cross-Adaptability data – Other major challenge that needs to be addressed by training and testing with different platforms of data/different devices as proposed by [25].”
Deep Learning for Sensor-based Human Activity Recognition (2020, background): “ impractical when sensor types and positions are not fixed. For instance, KL divergence is minimized between the parameters of CNNs which are trained by the old data and the new data, respectively in [72]. In order to address the issue mentioned, Akbari and Jafari [2] designed stochastic features th”
Recent trends in machine learning for human activity recognition—A survey (2018, background): “Investigating cross-domain transfer and deep learning to accommodate heterogeneity in the learned models are potential future directions in AR (Khan & Roy, 2018; Khan, Roy, & Misra, 2018).”