Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles
Abstract The era of Big Data has arrived. Recently, under the environment of intelligent
transportation systems (ITS) and connected/automated vehicles (CAV), Big Data has been …
transportation systems (ITS) and connected/automated vehicles (CAV), Big Data has been …
Traffic accident detection and condition analysis based on social networking data
Accurate detection of traffic accidents as well as condition analysis are essential to
effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be …
effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be …
Learning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation
Due to its wide applications, remote sensing (RS) image semantic segmentation has
attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …
attracted increasing research interest in recent years. Benefiting from its hierarchical abstract …
Earth observation for sustainable infrastructure: A review
Infrastructure is a fundamental sector for sustainable development and Earth observation
has great potentials for sustainable infrastructure development (SID). However …
has great potentials for sustainable infrastructure development (SID). However …
Understanding the potential of emerging digital technologies for improving road safety
Abstract Each year, 1.35 million people are killed on the world's roads and another 20–50
million are seriously injured. Morbidity or serious injury from road traffic collisions is …
million are seriously injured. Morbidity or serious injury from road traffic collisions is …
CovidSens: a vision on reliable social sensing for COVID-19
With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming
inherently important to disseminate accurate and timely information about the disease. Due …
inherently important to disseminate accurate and timely information about the disease. Due …
Crowdlearn: A crowd-ai hybrid system for deep learning-based damage assessment applications
Artificial Intelligence (AI) has been widely adopted in many important application domains
such as speech recognition, computer vision, autonomous driving, and AI for social good. In …
such as speech recognition, computer vision, autonomous driving, and AI for social good. In …
SPGAN-DA: Semantic-preserved generative adversarial network for domain adaptive remote sensing image semantic segmentation
Unsupervised domain adaptation for remote sensing semantic segmentation seeks to adapt
a model trained on the labeled source domain to the unlabeled target domain. One of the …
a model trained on the labeled source domain to the unlabeled target domain. One of the …
A comprehensive survey on mobile crowdsensing systems
Abstract In recent times, Mobile Crowdsensing (MCS) has garnered considerable attention
and emerged as a promising sensing paradigm. The MCS approach leverages the …
and emerged as a promising sensing paradigm. The MCS approach leverages the …
A multi-modal graph neural network approach to traffic risk forecasting in smart urban sensing
Forecasting traffic accidents at a fine-grained spatial scale is essential to provide effective
precautions and improve traffic safety in smart urban sensing applications. Current solutions …
precautions and improve traffic safety in smart urban sensing applications. Current solutions …