Spatio-Temporal Prediction of Baltimore Crime Events Using CLSTM Neural Networks

Spatio-Temporal Prediction of Baltimore Crime Events Using CLSTM Neural Networks

Crime activity in many cities worldwide causes significant damages to the lives of victims and their surrounding communities. It is a public disorder problem, and big cities experience large amounts of crime events. Spatio-temporal prediction of crimes activity can help the cities to have a better a...

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Bibliographic Details
Main Authors: Nicolas Esquivel, Orietta Nicolis, Billy Peralta, Jorge Mateu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
CNN and LSTM neural networks
crime prediction
deep learning
spatial and temporal structure
Online Access:https://ieeexplore.ieee.org/document/9252093/

Internet

https://ieeexplore.ieee.org/document/9252093/

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