Human-centred artificial intelligence for mobile health sensing: challenges and opportunities
Advances in wearable sensing and mobile computing have enabled the collection of health
and well-being data outside of traditional laboratory and hospital settings, paving the way for …
and well-being data outside of traditional laboratory and hospital settings, paving the way for …
A survey on uncertainty quantification methods for deep neural networks: An uncertainty source perspective
Deep neural networks (DNNs) have achieved tremendous success in making accurate
predictions for computer vision, natural language processing, as well as science and …
predictions for computer vision, natural language processing, as well as science and …
Cross-area travel time uncertainty estimation from trajectory data: a federated learning approach
Along with urbanization and the deployment of GPS sensors in vehicles and mobile phones,
massive amounts of trajectory data have been generated for city areas. The analysis of …
massive amounts of trajectory data have been generated for city areas. The analysis of …
A survey of distance-based vessel trajectory clustering: Data pre-processing, methodologies, applications, and experimental evaluation
Vessel trajectory clustering, a crucial component of the maritime intelligent transportation
systems, provides valuable insights for applications such as anomaly detection and …
systems, provides valuable insights for applications such as anomaly detection and …
A benchmark for computational analysis of animal behavior, using animal-borne tags
B Hoffman, M Cusimano, V Baglione, D Canestrari… - Movement Ecology, 2024 - Springer
Background Animal-borne sensors ('bio-loggers') can record a suite of kinematic and
environmental data, which are used to elucidate animal ecophysiology and improve …
environmental data, which are used to elucidate animal ecophysiology and improve …
Prediction of traffic state variability with an integrated model-based and data-driven Bayesian framework
Deriving statistical description of uncertainties associated with prediction of traffic states is
essential to development of reliability-based intelligent transportation systems. This paper …
essential to development of reliability-based intelligent transportation systems. This paper …
Traj2Former: A Local Context-aware Snapshot and Sequential Dual Fusion Transformer for Trajectory Classification
The wide use of mobile devices has led to a proliferated creation of extensive trajectory data,
rendering trajectory classification increasingly vital and challenging for downstream …
rendering trajectory classification increasingly vital and challenging for downstream …
Towards Uncertainty Quantification for Time Series Segmentation
E Draayer, H Cao - Proceedings of the 33rd ACM International …, 2024 - dl.acm.org
Time Series Segmentation (TSS) is a data mining task widely used in many applications to
generate a set of change points for a time series. Current TSS performance analyses focus …
generate a set of change points for a time series. Current TSS performance analyses focus …
[HTML][HTML] Designing a novel network anomaly detection framework using multi-serial stacked network with optimal feature selection procedures over DDOS attacks
KJ Pradeep, PK Shukla - International Journal of Intelligent Networks, 2025 - Elsevier
Distributed denial-of-service (DDoS) attacks are the major threat that disrupts the services in
the computer system and networks using traffic and targeted sources. So, real-world attack …
the computer system and networks using traffic and targeted sources. So, real-world attack …
On Splitting Raw Trajectories
With the surge of data-driven solutions for trajectory analysis operations, the need for
accurate trajectory trip data has spiked. However, the available datasets are raw trajectories …
accurate trajectory trip data has spiked. However, the available datasets are raw trajectories …