The rapid collaborative optimization (CO) has an increasing demand for high-fidelity
surrogate models. However, the traditional surrogate model cannot be applied to all working …

The ubiquity of smartphones equipped with multiple sensors has provided the possibility of
automatically recognizing of human activity, which can benefit intelligent applications such …

In this paper, we propose a brand new scene understanding paradigm called" Context
Graph Generation (CGG)", aiming at abstracting holistic semantic information in the …

Human context recognition (HCR) using sensor data is a crucial task in Context-Aware (CA)
applications in domains such as healthcare and security. Supervised machine learning HCR …

Human Activity Recognition (HAR) is a challenging, multi-label classification problem as
activities may co-occur and sensor signals corresponding to the same activity may vary in …

In the last few decades, major progress has been made in the medical field; in particular,
new treatments and advanced health technologies allow for considerable improvements in …

Human activity recognition (HAR), the task of predicting the activities performed by an
individual using mobile sensor data, is an active and important area of research …

There has recently been increased interest in context-aware mobile sensing applications
due to the ubiquity of sensor-rich smartphones. Our DARPA-funded Warfighter Analytics for …

In important domains from video stream analytics to human context recognition, datasets are
only partially-labeled. Worse yet, the labels are often applied sequentially, as annotators …

Sensor-based physical activity detection has become increasingly popular in recent years
due to the development of internet-of-things and smart sensing technologies, and a large …