Self-supervised pretraining and transfer learning enable\titlebreak flu and covid-19 predictions in small mobile sensing datasets
MA Merrill, T Althoff - Conference on Health, Inference, and …, 2023 - proceedings.mlr.press
Detailed mobile sensing data from phones and fitness trackers offer an opportunity to
quantify previously unmeasurable behavioral changes to improve individual health and …
quantify previously unmeasurable behavioral changes to improve individual health and …
Is sustained participation a myth in crowdsourcing? A review
Purpose The motivation to participate in crowdsourcing (CS) platforms is an emerging
challenge. Although researchers and practitioners have focused on crowd motivation in the …
challenge. Although researchers and practitioners have focused on crowd motivation in the …
Intersection of machine learning and mobile crowdsourcing: a systematic topic-driven review
During the past decade of the big data era, mobile crowdsourcing has emerged as a popular
research area, leveraging the collective intelligence and engagement of a vast number of …
research area, leveraging the collective intelligence and engagement of a vast number of …
Predicting performance improvement of human activity recognition model by additional data collection
K Tanigaki, TC Teoh, N Yoshimura… - Proceedings of the …, 2022 - dl.acm.org
The development of a machine-learning-based human activity recognition (HAR) system
using body-worn sensors is mainly composed of three phases: data collection, model …
using body-worn sensors is mainly composed of three phases: data collection, model …
Urban-scale poi updating with crowd intelligence
Points of Interest (POIs), such as entertainment, dining, and living, are crucial for urban
planning and location-based services. However, the high dynamics and expensive updating …
planning and location-based services. However, the high dynamics and expensive updating …
Homekit2020: A benchmark for time series classification on a large mobile sensing dataset with laboratory tested ground truth of influenza infections
Despite increased interest in wearables as tools for detecting various health conditions,
there are not as of yet any large public benchmarks for such mobile sensing data. The few …
there are not as of yet any large public benchmarks for such mobile sensing data. The few …
A stacked CNN and random forest ensemble architecture for complex nursing activity recognition and nurse identification
Nursing activity recognition has immense importance in the development of smart
healthcare management and is an extremely challenging area of research in human activity …
healthcare management and is an extremely challenging area of research in human activity …
CrossHAR: Generalizing Cross-dataset Human Activity Recognition via Hierarchical Self-Supervised Pretraining
The increasing availability of low-cost wearable devices and smartphones has significantly
advanced the field of sensor-based human activity recognition (HAR), attracting …
advanced the field of sensor-based human activity recognition (HAR), attracting …
Human-centred design on crowdsourcing annotation towards improving active learning model performance
Active learning in machine learning is an effective approach to reducing the cost of human
efforts for generating labels. The iterative process of active learning involves a human …
efforts for generating labels. The iterative process of active learning involves a human …
Analysis of Motivational Theories in Crowdsourcing Using Long Tail Theory: A Systematic Literature Review
Motivational theories have been extensively studied in a wide range of fields, such as
medical sciences, business, management, physiology, sociology, and particularly in the …
medical sciences, business, management, physiology, sociology, and particularly in the …