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Embrapa Wine Grape Instance Segmentation Dataset – Embrapa WGISD

Thiago Santos; de Souza, Leonardo; dos Santos Andreza; Avila, Sandra


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    "description": "<p><strong>Embrapa Wine Grape Instance Segmentation Dataset &ndash; Embrapa WGISD</strong></p>\n\n<p>For a detailed description of this dataset, following the <em>datasheet for the datasets</em> recommendation proposed by <a href=\"https://arxiv.org/abs/1803.09010\">Gebru et al.</a>, check the <strong>README.md</strong> file.</p>\n\n<p><strong>Motivation for Dataset Creation</strong></p>\n\n<p><em>Why was the dataset created?</em></p>\n\n<p>Embrapa WGISD (<em>Wine Grape Instance Segmentation Dataset</em>) was created to provide images and annotation to study <em>object detection and instance segmentation</em> for image-based monitoring and field robotics in viticulture. It provides instances from five different grape varieties taken on field. These instances shows variance in grape pose,<br>\nillumination and focus, including genetic and phenological variations such as shape, color and compactness.</p>\n\n<p><em>What (other) tasks could the dataset be used for?</em></p>\n\n<p>Possible uses include relaxations of the instance segmentation problem: classification (Is a grape in the image?), semantic segmentation (What are the &quot;grape pixels&quot; in the image?), and object detection (Where are the grapes in the image?). The WGISD can also be used in grape variety identification.</p>\n\n<p>&nbsp;</p>", 
    "language": "eng", 
    "title": "Embrapa Wine Grape Instance Segmentation Dataset \u2013 Embrapa WGISD", 
    "license": {
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    "notes": "The building of the WGISD dataset was supported by the Embrapa SEG Project 01.14.09.001.05.04, Image-based metrology for Precision Agriculture and Phenotyping, and the CNPq PIBIC Program (grants 161165/2017-6 and 125044/2018-6).", 
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    "version": "1.0.0", 
    "references": [
      "Santos, T.T., Souza, L.L., Santos, A.M., & Avila, S.E. (2019). Grape detection, segmentation and tracking using deep neural networks and three-dimensional association. ArXiv, abs/1907.11819."
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    "keywords": [
      "instance segmentation", 
      "object detection", 
      "viticulture", 
      "agriculture"
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    "publication_date": "2019-07-26", 
    "creators": [
      {
        "orcid": "0000-0002-9272-3403", 
        "affiliation": "Embrapa Agricultural Informatics", 
        "name": "Thiago Santos"
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      {
        "affiliation": "University of Campinas", 
        "name": "de Souza, Leonardo"
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      {
        "name": "dos Santos Andreza"
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        "affiliation": "University of Campinas", 
        "name": "Avila, Sandra"
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