1 code implementation • 31 Jul 2022 • Shohreh Deldari, Hao Xue, Aaqib Saeed, Daniel V. Smith, Flora D. Salim
Contrastive Learning (CL) is one of the most well-known approaches in SSL that attempts to learn general, informative representations of data.
no code implementations • 6 Jun 2022 • Shohreh Deldari, Hao Xue, Aaqib Saeed, Jiayuan He, Daniel V. Smith, Flora D. Salim
Unlike existing reviews of SSRL that have pre-dominately focused upon methods in the fields of CV or NLP for a single modality, we aim to provide the first comprehensive review of multimodal self-supervised learning methods for temporal data.
2 code implementations • 28 Nov 2020 • Shohreh Deldari, Daniel V. Smith, Hao Xue, Flora D. Salim
Change Point Detection (CPD) methods identify the times associated with changes in the trends and properties of time series data in order to describe the underlying behaviour of the system.
1 code implementation • 24 Jul 2020 • Shohreh Deldari, Daniel V. Smith, Amin Sadri, Flora D. Salim
Extracting informative and meaningful temporal segments from high-dimensional wearable sensor data, smart devices, or IoT data is a vital preprocessing step in applications such as Human Activity Recognition (HAR), trajectory prediction, gesture recognition, and lifelogging.
Ranked #3 on Change Point Detection on TSSB (Covering metric)