Tipo di tesi
Tesi di laurea magistrale
Titolo
Quantized Convolutional Neural Networks for Real-Time Vehicle Tracking
Corso di studi
INFORMATICA
Parole chiave
- convolutional neural network
- noise pollution
- quantization
- real-time
- traffic flow
- vehicle tracking
Data inizio appello
12/04/2024
Consultabilità
Non consultabile
Data di rilascio
12/04/2027
Riassunto (Italiano)
Traffic flow and speed are among the most important parameters needed to be estimated when studying noise pollution. In this thesis, a real-time multiple-vehicle recognition system was developed using a low-cost system consisting of a quantized convolutional network with a tracking algorithm, capable of counting the amount of vehicles passing through and their associated acceleration and speed information.
The results obtained through the proposed methodology provide a low-cost but yet powerful tool for the corresponding authorities involved in the task of noise pollution assessment.
