Heudiasyc - UMR CNRS 7253
Université de technologie de Compiègne
CS 60319 - 57 avenue de Landshut
60203 COMPIEGNE CEDEX - FRANCE
CS 60319 - 57 avenue de Landshut
60203 COMPIEGNE CEDEX - FRANCE
Ce portail permet l'exploitation des données expérimentales acquises au sein du laboratoire Heudiasyc.
Heudiasyc (HEUristique et DIAgnostic des SYstèmes Complexes) est un laboratoire géré conjoitement par l'Université de Technologie de Compiègne et le CNRS.
Il opère dans le domaine des sciences de l'information et du numérique, à savoir l'informatique, l'automatique, la robotique et l'intelligence artificielle.
Il y a actuellement 14 projets contenant 118 jeux de données depuis 2018.
Dernières mises à jour :
14/01/2025 -
Automatic Image Annotation for Mapped Features Detection
Dataset used in the article "Automatic Image Annotation for Mapped Features Detection"...
14/05/2024 -
Learning to Estimate Two Dense Depths from LiDAR and Event Data
This project contains the data used as part of the "Learning to Estimate Two Dense Depths from LiDAR and Event Data" article, publishe...
14/07/2023 -
Infinity
Please find details and refer to this article if you use those data: Full reference and DOI will be communicated soon.
Two experi...
04/10/2024 -
Dataset for object detection
Contain all images and pointwise annotations used to train YOLOv7 pole base detectors and the obtained weights.
14/05/2024 -
The Synthetic LiDAR Events Depths (SLED) Dataset
The Synthetic LiDAR Events Depths (SLED) Dataset, as described in the "Learning to Estimate Two Dense Depths from LiDAR and Event Data"...
14/06/2023 -
Within subject design (experiment 2)
Data from 31 subjects
29/01/2025 -
All data for automatic annotation
Regroups all the data needed to recompute map-based, segmentation-based and lidar-based annotations in a unique zip file
29/01/2025 -
All data for training and validation
Contains all images and labels used for training and validation. The label files include the positions of the pole bases. To train a YOLO detect...
04/10/2024 -
Validation set
939 images, manual pointwise annotations and automatic pointwise annotations from map-based, image segmentation-based and lidar-based methods
Mise en avant :
This dataset comprises labelled LIDAR scans, which were acquired in 6 locations in France by Renault and Heudiasyc Lab, both members of the joint Lab SIVALab. Each LIDAR point is labelled with t...
This dataset was recorded for cooperative localization with a platoon of two Renault Zoés on the UTC Séville test track. Each vehicle is equipped with a low-cost mono-frequenc...
Datasets generated based on INFOCA institution data for the firefighters timetabling problem FFTP