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

Metadata Updated: February 4, 2022

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

Downloads & Resources


Metadata Created Date November 10, 2020
Metadata Updated Date February 4, 2022

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date November 10, 2020
Metadata Updated Date February 4, 2022
Publisher Agricultural Research Service
Identifier e270dc1b-f9b2-4818-b8ee-7bcc7271e6ff
Data Last Modified 2019-08-05
Public Access Level public
Bureau Code 005:18
Metadata Context
Schema Version
Catalog Describedby
Harvest Object Id a11975a8-7a08-4d8f-ba54-ce42d06fe139
Harvest Source Id d3fafa34-0cb9-48f1-ab1d-5b5fdc783806
Harvest Source Title USDA JSON
Old Spatial {"type":"Point","coordinates":-77.87,39.35}
Program Code 005:040
Source Datajson Identifier True
Source Hash 35bad29a5c380c85fe2f3dc9bb2bf10f7330b2da
Source Schema Version 1.1
Spatial {"type":"Point","coordinates":-77.87,39.35}

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