Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a personâs activities and signiïŹ...
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract a personâs activities and signiïŹcant plac...
Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people...
Sunny Consolvo, David W. McDonald, Tammy Toscos, M...
AbstractâWe propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...