11 papers
Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach
Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe
The use of HSI for autonomous navigation is a promising research field aimed at improving the accuracy and robustness of detection, tracking, and scene understanding systems based…
Balancing Robustness and Efficiency in Embedded DNNs Through Activation Function Selection
Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe
Machine learning-based embedded systems for safety-critical applications, such as aerospace and autonomous driving, must be robust to perturbations caused by soft errors. As transi…
Reliable Explainability of Deep Learning Spatial-Spectral Classifiers for Improved Semantic Segmentation in Autonomous Driving
Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe
Integrating hyperspectral imagery (HSI) with deep neural networks (DNNs) can strengthen the accuracy of intelligent vision systems by combining spectral and spatial information, wh…
Analysis of the Motion Sickness and the Lack of Comfort in Car Passengers
Estibaliz Asua, Jon Gutiérrez-Zaballa, Ãscar Mata-Carballeira +2
Advanced driving assistance systems (ADAS) are primarily designed to increase driving safety and reduce traffic congestion without paying too much attention to passenger comfort or…
An FPGA-Based Neuro-Fuzzy Sensor for Personalized Driving Assistance
Ãscar Mata-Carballeira, Jon Gutiérrez-Zaballa, Inés del Campo +1
Advanced driving-assistance systems (ADAS) are intended to automatize driver tasks, as well as improve driving and vehicle safety. This work proposes an intelligent neuro-fuzzy sen…
Exploring Fully Convolutional Networks for the Segmentation of Hyperspectral Imaging Applied to Advanced Driver Assistance Systems
Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe +2
Advanced Driver Assistance Systems (ADAS) are designed with the main purpose of increasing the safety and comfort of vehicle occupants. Most of current computer vision-based ADAS p…