HMGAN: A hierarchical multi-modal generative adversarial network model for wearable human activity recognition
Wearable Human Activity Recognition (WHAR) is an important research field of ubiquitous
and mobile computing. Deep WHAR models suffer from the overfitting problem caused by …
and mobile computing. Deep WHAR models suffer from the overfitting problem caused by …
Har-ctgan: a mobile sensor data generation tool for human activity recognition
J DeOliveira, W Gerych, A Koshkarova… - … Conference on Big …, 2022 - ieeexplore.ieee.org
Human activity recognition (HAR) is the process of using mobile sensor data to determine
the physical activities performed by individuals. HAR is the backbone of many mobile …
the physical activities performed by individuals. HAR is the backbone of many mobile …
Experience: A Comparative Analysis of Multivariate Time-Series Generative Models: A Case Study on Human Activity Data
Human activity recognition (HAR) is an active research field that has seen great success in
recent years due to advances in sensory data collection methods and activity recognition …
recent years due to advances in sensory data collection methods and activity recognition …
Human Activity Prediction Using Generative Adversarial Networks
A Shete, A Gupta, A Waghumbare… - 2024 15th …, 2024 - ieeexplore.ieee.org
This paper introduces an innovative approach to enhance human activity prediction by
integrating Temporal Convolutional Networks (TCN) with an Encoder-Decoder model within …
integrating Temporal Convolutional Networks (TCN) with an Encoder-Decoder model within …
[PDF][PDF] A comprehensive guideline for Human Activity Recognition with Deep Learning
P Andreadis, M Shumska - 19th SC@ RUG 2021-2022 - core.ac.uk
Human Activity Recognition (HAR) is the challenging problem of automatically identifying
actions performed by individuals during their day-to-day routine, formulated as time-series …
actions performed by individuals during their day-to-day routine, formulated as time-series …