STranGAN: Adversarially-learnt Spatial Transformer for scalable human activity recognition

• Main Authors: Faridee, Abu Zaher Md, Chakma, Avijoy, MISRA, Archan, Roy, Nirmalya
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Adversarial learning; Domain adaptation; Generative modeling; Learnable data augmentation; Wearable sensing; Numerical Analysis and Scientific Computing; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/6946; https://ink.library.smu.edu.sg/context/sis_research/article/7949/viewcontent/Strangan_av.pdf
• Institution: Singapore Management University

We tackle the problem of domain adaptation for inertial sensing-based human activity recognition (HAR) applications -i.e., in developing mechanisms that allow a classifier trained on sensor samples collected under a certain narrow context to continue to achieve high activity recognition accuracy eve...