A device can receive GPS data or values for a set of metrics at a set of GPS points that form a GPS track of a vehicle. The device can determine additional values for additional metrics using the GPS data or the values for the set of metrics. The device can determine a set of vectors for the set of GPS points using the GPS data, the values, or the additional values. The set of vectors can be used in a recurrent neural network (RNN) to classify the vehicle. The device can process the set of vectors via one or more sets of RNN layers of the RNN. The device can determine a classification of the vehicle using a result of processing the set of vectors. The result can be output by the output layer. The device can perform an action based on the classification of the vehicle.

Vehicle classification using a recurrent neural network (RNN)

Samuele Salti;
2018

Abstract

A device can receive GPS data or values for a set of metrics at a set of GPS points that form a GPS track of a vehicle. The device can determine additional values for additional metrics using the GPS data or the values for the set of metrics. The device can determine a set of vectors for the set of GPS points using the GPS data, the values, or the additional values. The set of vectors can be used in a recurrent neural network (RNN) to classify the vehicle. The device can process the set of vectors via one or more sets of RNN layers of the RNN. The device can determine a classification of the vehicle using a result of processing the set of vectors. The result can be output by the output layer. The device can perform an action based on the classification of the vehicle.
US10345449
Samuele Salti, Francesco Sambo, Leonardo Taccari, Luca Bravi, Matteo Simoncini, Alessandro Lori
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/741096
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