Annotated image dataset of household objects from the RoboFEI@Home team

Annotated image dataset of household objects from the RoboFEI@Home teamThis data set contains two sets of pictures of household objects, created by the RoboFEI@Home team to develop object detection systems for a domestic robot.The first data set was created with objects from a local supermarket. Pro...

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Hauptverfasser: Meneghetti, Douglas De Rizzo, Domingues, Pedro Henrique Silva, Perez, Bruno de Freitas Vece, Meyer, Thiago Spilborghs Bueno, Cardoso, Kimberlin Kariny Gonçalves, de Lima, Amanda Maciel, Gonbata, Marina Yukari, Pimentel, Fagner de Assis Moura, Aquino Junior, Plinio Thomaz
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creator Meneghetti, Douglas De Rizzo
Domingues, Pedro Henrique Silva
Perez, Bruno de Freitas Vece
Meyer, Thiago Spilborghs Bueno
Cardoso, Kimberlin Kariny Gonçalves
de Lima, Amanda Maciel
Gonbata, Marina Yukari
Pimentel, Fagner de Assis Moura
Aquino Junior, Plinio Thomaz
description Annotated image dataset of household objects from the RoboFEI@Home teamThis data set contains two sets of pictures of household objects, created by the RoboFEI@Home team to develop object detection systems for a domestic robot.The first data set was created with objects from a local supermarket. Product brands are typical from Brazil. The second data set is composed of objects from the RoboCup@Home 2018 OPL competition.The data set contains the basic resources for the creation of custom object detection systems. Users can use the provided annotated images to train their own models and validate them in a set of test images, or they can analyze the inference time of the proposed methods in the provided videos.Example videos of detection systems trained with this data set can be found in the following links:https://www.youtube.com/watch?v=Py6_qG52EYQhttps://www.youtube.com/watch?v=fXJYmJOaSxQ
doi_str_mv 10.21227/sh59-fs52
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identifier DOI: 10.21227/sh59-fs52
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subjects Artificial Intelligence
Computer Vision
Machine Learning
object detection
title Annotated image dataset of household objects from the RoboFEI@Home team
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