Semi-Supervised Contrastive Learning for Human Activity Recognition

Recent developments in deep learning have motivated the use of deep neural networks in mobile sensing applications. Human Activity Recognition (HAR), as one of the most important mobile sensing applications, has enjoyed great success due to the utilization of deep neural networks. Motivated by the success of self-supervised learning frameworks in computer vision and natural language processing, se...