Zobrazeno 1 - 10
of 409
pro vyhledávání: '"P, Zaballa"'
Autor:
Gutiérrez-Zaballa, Jon, Basterretxea, Koldo, Echanobe, Javier, Martínez, M. Victoria, del Campo, Inés
Publikováno v:
Design and Architecture for Signal and Image Processing (DASIP 2022)
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 perform detection and tracking tasks quite successfully under regular c
Externí odkaz:
http://arxiv.org/abs/2412.03982
Publikováno v:
2024 39th Conference on Design of Circuits and Integrated Systems (DCIS)
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 errors. Soft errors are an increasing concern in modern digital process
Externí odkaz:
http://arxiv.org/abs/2412.03682
Publikováno v:
2024 Journal of Systems Architecture (JSA)
As the deployment of artifical intelligence (AI) algorithms at edge devices becomes increasingly prevalent, enhancing the robustness and reliability of autonomous AI-based perception and decision systems is becoming as relevant as precision and perfo
Externí odkaz:
http://arxiv.org/abs/2412.03630
Autor:
Gutiérrez-Zaballa, Jon, Basterretxea, Koldo, Echanobe, Javier, Martínez, M. Victoria, Martínez-Corral, Unai, Carballeira, Óscar Mata, del Campo, Inés
Publikováno v:
2023 Journal of Systems Architecture (JSA)
Most of current computer vision-based advanced driver assistance systems (ADAS) perform detection and tracking of objects quite successfully under regular conditions. However, under adverse weather and changing lighting conditions, and in complex sit
Externí odkaz:
http://arxiv.org/abs/2411.19274
Autor:
Gutiérrez-Zaballa, Jon, Basterretxea, Koldo, Echanobe, Javier, Mata-Carballeira, Óscar, Martínez, M. Victoria
Publikováno v:
2023 30th IEEE International Conference on Electronics, Circuits and Systems (ICECS)
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 driving. The work addresses the challenges of shaping and deploying mu
Externí odkaz:
http://arxiv.org/abs/2411.17543
Autor:
Gutiérrez-Zaballa, Jon, Basterretxea, Koldo, Echanobe, Javier, Martínez, M. Victoria, Martínez-Corral, Unai
Publikováno v:
2023 IEEE Symposium Series on Computational Intelligence (SSCI)
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 annotated images from videos recorded during winter and fall in real driving
Externí odkaz:
http://arxiv.org/abs/2411.17530
Autor:
Zaballa, Vincent D., Hui, Elliot E.
Recent advances in generative deep learning have transformed small molecule design, but most methods lack biological systems context, focusing narrowly on specific protein pockets. We introduce a non-differentiable diffusion guidance method that inte
Externí odkaz:
http://arxiv.org/abs/2410.10108
Autor:
Zaballa, Vincent D., Hui, Elliot E.
Systems biology models are useful models of complex biological systems that may require a large amount of experimental data to fit each model's parameters or to approximate a likelihood function. These models range from a few to thousands of paramete
Externí odkaz:
http://arxiv.org/abs/2407.08612
Rosenbrock's theorem on polynomial system matrices is a classical result in linear systems theory that relates the Smith-McMillan form of a rational matrix $G$ with the Smith forms of an irreducible polynomial system matrix $P$ giving rise to $G$ and
Externí odkaz:
http://arxiv.org/abs/2406.18218
Autor:
Zaballa, Vincent D., Hui, Elliot E.
Systems biology relies on mathematical models that often involve complex and intractable likelihood functions, posing challenges for efficient inference and model selection. Generative models, such as normalizing flows, have shown remarkable ability
Externí odkaz:
http://arxiv.org/abs/2312.02391