most citedOn-chip Hyperspectral Image Segmentation with Fully Convolutional Networks for Scene Understanding in Autonomous Driving

35 citations · 92 across the 6 of their papers we have counts for

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cs.CV202410 cited

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.CV202422 cited

Evaluating Single Event Upsets in Deep Neural Networks for Semantic Segmentation: an embedded system perspective

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe

As the deployment of artifical intelligence (AI) algorithms at edge devices becomes increasingly prevalent, enhancing the robustness and reliability of autonomous AI-based percepti…

cs.CV202435 cited

On-chip Hyperspectral Image Segmentation with Fully Convolutional Networks for Scene Understanding in Autonomous Driving

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe +4

Most of current computer vision-based advanced driver assistance systems (ADAS) perform detection and tracking of objects quite successfully under regular conditions. However, unde…

cs.CV20245 cited

Rapid Deployment of Domain-specific Hyperspectral Image Processors with Application to Autonomous Driving

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe +2

The article discusses the use of low cost System-On-Module (SOM) platforms for the implementation of efficient hyperspectral imaging (HSI) processors for application in autonomous…

cs.CV202418 cited

HSI-Drive v2.0: More Data for New Challenges in Scene Understanding for Autonomous Driving

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe +2

We present the updated version of the HSI-Drive dataset aimed at developing automated driving systems (ADS) using hyperspectral imaging (HSI). The v2.0 version includes new annotat…