Scientific Research Publishing

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case Study of Guangzhou South Railway Station ()

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...
IEEE

Enhancing Automated Seizure Detection via Self-Calibrating Spatial-Temporal EEG Features with SC-LSTM

Abstract: Epilepsy, a highly individualized neurological disorder, affects millions globally. Electroencephalography (EEG) remains the cornerstone for seizure diagnosis, yet manual interpretation is ...
Frontiers

4D trajectory lightweight prediction algorithm based on knowledge distillation technique

1 Civil Aviation Ombudsman Training College, Civil Aviation Flight University of China, Guanghan, China 2 College of Air Traffic Management, Civil Aviation Flight University of China, Chengdu, China ...
Digital Trends

A macOS feature few people use just got even better

I religiously scour the Mac user forums and communities to find the latest tools and utilities, especially those in the realm of open-source software. Apps like Maccy and Swift have become a part of ...
C&EN

SOH Estimation Based on Multisource Feature Extraction and SSA-LSTM Algorithm

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...
IEEE

Complex Landscape Rice Extraction Using Integrated Sentinel-2 Spectral–Temporal–Spatial Imagery and a Hybrid Deep Learning Architecture

Abstract: Rice extraction in complex landscapes is a challenging issue in remote sensing, particularly in areas with diverse land-use types and spatiotemporal variability. To enhance the accuracy of ...
Frontiers

MRGS-LSTM: a novel multi-site wind speed prediction approach with spatio-temporal correlation

The wind energy industry is witnessing a new era of extraordinary growth as the demand for renewable energy continues to grow. However, accurately predicting wind speed remains a significant challenge ...
Microsoft

Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks

Skeleton based action recognition distinguishes human actions using the trajectories of skeleton joints, which provide a very good representation for describing actions. Considering that recurrent ...