118 citations · 131 across the 8 of their papers we have counts for
9 papers
Coverage You Can Steer: Online Conformal Calibration for RL-Driven Hardware-Aware NAS
Pedro Brandimarte, Nerea Aranjuelo, Marcos Nieto +1
Hardware-aware neural architecture search (NAS) is dominated by evaluation cost: every architecture must be trained before its reward is known. Conformal-prediction filters cut thi…
Exploration of VLMs for Driver Monitoring Systems Applications
Paola Natalia Cañas, Marcos Nieto, Oihana Otaegui +1
In recent years, we have witnessed significant progress in emerging deep learning models, particularly Large Language Models (LLMs) and Vision-Language Models (VLMs). These models…
Monetisation of and Access to in-Vehicle data and resources: the 5GMETA approach
Djibrilla Amadou Kountche, Fatma Raissi, Mandimby Ranaivo Rakotondravelona +5
Today's vehicles are increasingly embedded with computers and sensors which produce huge amount of data. The data are exploited for internal purposes and with the development of co…
Virtual passengers for real car solutions: synthetic datasets
Paola Natalia Canas, Juan Diego Ortega, Marcos Nieto +1
Strategies that include the generation of synthetic data are beginning to be viable as obtaining real data can be logistically complicated, very expensive or slow. Not only the cap…
RTMaps-based Local Dynamic Map for multi-ADAS data fusion
Marcos Nieto, Mikel Garcia, Itziar Urbieta +1
Work on Local Dynamic Maps (LDM) implementation is still in its early stages, as the LDM standards only define how information shall be structured in databases, while the mechanism…
5G Features and Standards for Vehicle Data Exploitation
Gorka Velez, Edoardo Bonetto, Daniele Brevi +6
Cars capture and generate huge volumes of data in real-time about the driving dynamics, the environment, and the driver and passengers' activities. Due to the proliferation of coop…
DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis
Juan Diego Ortega, Neslihan Kose, Paola Cañas +5
Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of suffici…
3D Object Detection From LiDAR Data Using Distance Dependent Feature Extraction
Guus Engels, Nerea Aranjuelo, Ignacio Arganda-Carreras +2
This paper presents a new approach to 3D object detection that leverages the properties of the data obtained by a LiDAR sensor. State-of-the-art detectors use neural network archit…
Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey
Gorka Velez, Oihana Otaegui
Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role…