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Autori principali: Sánchez González, Lidia, Mayoko, Jean Chrysostome
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2025
Accesso online:https://doi.org/10.5281/zenodo.16537441
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author Sánchez González, Lidia
Mayoko, Jean Chrysostome
author_facet Sánchez González, Lidia
Mayoko, Jean Chrysostome
contents <p>This dataset enables real-time object detection of sheep, wolves, dogs, wild dog, redfox, fox, coyote, cow and humans for robotic shepherding applications. Built from raw YOLOv5-style sources, it integrates <strong>class balancing</strong>, <strong>video-based diversity</strong>, and <strong>strong augmentations</strong> to enhance robustness. A <strong>recycling strategy</strong> is used for rare classes. Compatible with YOLOv5 to YOLOv12, RT-DETR, and ROS 2 deployments on legged robots, the dataset includes labels, images, statistics, and visualizations, ready for direct use in training detection models for autonomous livestock protection.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_16537441
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Augmented and Diverse Herding Dataset for Autonomous Shepherd Robots
Sánchez González, Lidia
Mayoko, Jean Chrysostome
<p>This dataset enables real-time object detection of sheep, wolves, dogs, wild dog, redfox, fox, coyote, cow and humans for robotic shepherding applications. Built from raw YOLOv5-style sources, it integrates <strong>class balancing</strong>, <strong>video-based diversity</strong>, and <strong>strong augmentations</strong> to enhance robustness. A <strong>recycling strategy</strong> is used for rare classes. Compatible with YOLOv5 to YOLOv12, RT-DETR, and ROS 2 deployments on legged robots, the dataset includes labels, images, statistics, and visualizations, ready for direct use in training detection models for autonomous livestock protection.</p>
title Augmented and Diverse Herding Dataset for Autonomous Shepherd Robots
url https://doi.org/10.5281/zenodo.16537441