activity
20242026
collaborators

10 papers

cs.CV2026

Challenges in Hyperspectral Imaging for Autonomous Driving: The HSI-Drive Case

Koldo Basterretxea, Jon Gutiérrez-Zaballa, Javier Echanobe

The use of hyperspectral imaging (HSI) in autonomous driving (AD), while promising, faces many challenges related to the specifics and requirements of this application domain. On t…

cs.CV2025

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…

cs.LG2025

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…

eess.IV2025

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…

cs.CV2024

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…

cs.LG2024

Designing DNNs for a trade-off between robustness and processing performance in embedded devices

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe

Machine learning-based embedded systems employed in safety-critical applications such as aerospace and autonomous driving need to be robust against perturbations produced by soft e…