[HTML][HTML] Enhancing road safety with machine learning: Current advances and future directions in accident prediction using non-visual data
Road traffic accident (RTA) poses a significant road safety issue due to the increased
fatalities worldwide. To address it, various artificial intelligence solutions are developed to …
fatalities worldwide. To address it, various artificial intelligence solutions are developed to …
A systematic literature review of learning-based traffic accident prediction models based on heterogeneous sources
Statistics affirm that almost half of deaths in traffic accidents were vulnerable road users,
such as pedestrians, cyclists, and motorcyclists. Despite the efforts in technological …
such as pedestrians, cyclists, and motorcyclists. Despite the efforts in technological …
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 …
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 …
CrowdGraph: A crowdsourcing multi-modal knowledge graph approach to explainable fauxtography detection
Human-centric fauxtography is a category of multi-modal posts that spread misleading
information on online information distribution and sharing platforms such as online social …
information on online information distribution and sharing platforms such as online social …
CompDrone: towards integrated computational model and social drone based wildfire monitoring
Forest fires cause irreversible damages worldwide every year. Monitoring wildfire
propagation is thus a vital task in mitigating forest fires. While computational model-based …
propagation is thus a vital task in mitigating forest fires. While computational model-based …
Utility-based route choice behavior modeling using deep sequential models
GPS-based navigation systems have played crucial roles to improve transportation system
performances. A limitation of such route guidance systems is that their route …
performances. A limitation of such route guidance systems is that their route …
Transres: a deep transfer learning approach to migratable image super-resolution in remote urban sensing
Recent advances in remote sensing provide a powerful and scalable sensing paradigm to
capture abundant visual information about the urban environments. We refer to such a …
capture abundant visual information about the urban environments. We refer to such a …
Social edge intelligence: Integrating human and artificial intelligence at the edge
In this vision paper, we propose a new concept," Social Edge Intelligence (SEI)", where the
artificial intelligence (AI) and human intelligence (HI) are tightly integrated to address a set of …
artificial intelligence (AI) and human intelligence (HI) are tightly integrated to address a set of …
Transland: An adversarial transfer learning approach for migratable urban land usage classification using remote sensing
Urban land usage classification is a critical task in big data based smart city applications that
aim to understand the social-economic land functions and physical land attributes in urban …
aim to understand the social-economic land functions and physical land attributes in urban …