Exploring single-head and multi-head CNN and LSTM-based models for road surface classification using on-board vehicle multi-IMU data

Exploring single-head and multi-head CNN and LSTM-based models for road surface classification using on-board vehicle multi-IMU data

Abstract Accurate road surface monitoring is essential for ensuring vehicle and pedestrian safety, and it relies on robust data acquisition and analysis methods. This study examines the classification of road surface conditions using single- and multi-head deep learning architectures, specifically C...

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Bibliographic Details
Main Authors: Luis A. Arce-Saenz, Javier Izquierdo-Reyes, Rogelio Bustamante-Bello
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Road Surface Condition Classification
Inertial Measurements
On-Board Sensing
Convolutional Neural Networks
Recurrent Neural Networks
Long Short-Term Memory
Online Access:https://doi.org/10.1038/s41598-025-10573-2
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