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...

Full description

Saved in:

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
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

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

Similar Items