Data from: Multi-species fruit flower detection using a refined semantic segmentation network

Metadata Updated: November 10, 2020

This dataset consists of four sets of flower images, from three different species: apple, peach, and pear, and accompanying ground truth images. The images were acquired under a range of imaging conditions. These datasets support work in an accompanying paper that demonstrates a flower identification algorithm that is robust to uncontrolled environments and applicable to different flower species. While this data is primarily provided to support that paper, other researchers interested in flower detection may also use the dataset to develop new algorithms. Flower detection is a problem of interest in orchard crops because it is related to management of fruit load. Funding provided through ARS Integrated Orchard Management and Automation for Deciduous Tree Fruit Crops.

Access & Use Information

Public: This dataset is intended for public access and use. License: Creative Commons CCZero

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Dates

Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020
Publisher Agricultural Research Service
Unique Identifier Unknown
Maintainer
Identifier e270dc1b-f9b2-4818-b8ee-7bcc7271e6ff
Data Last Modified 2019-08-05
Public Access Level public
Bureau Code 005:18
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
License https://creativecommons.org/publicdomain/zero/1.0/
Program Code 005:040
Source Datajson Identifier True
Source Hash 627715670935d1708078476db9efe9427a037e58
Source Schema Version 1.1
Spatial POINT (-77.87 39.35)

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