Data

Wheat Head Detection Ground-UAV Dataset

The University of Queensland
Mr Chris James (Aggregated by) Mr Chris James (Aggregated by) Professor Scott Chapman (Aggregated by) Professor Scott Chapman (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/f6a6b07&rft.title=Wheat Head Detection Ground-UAV Dataset&rft.identifier=RDM ID: fad03110-1c55-11ee-a458-8d4e0c4f9a55&rft.publisher=The University of Queensland&rft.description=This dataset consists of RGB images captured during late harvest stage of wheat plots at the University of Queensland's Gatton campus in November 2021. The dataset is divided into three subsets: 2 sets of images acquired using a UAV (Unmanned Aerial Vehicle) and a set of images captured with a ground camera. Each subset includes bounding box annotations for training and evaluating object detection models. The ground images in this dataset were captured using the OpenCV OAK-1 camera, positioned at a height of approximately 1.5 meters above the canopy. These images have a raw resolution of 2160x2160 pixels and a Ground Sampling Distance (GSD) of approximately 0.030 cm per pixel. The UAV images were acquired using the DJI Phantom 4 Pro drone, flying at an altitude of 10 meters. These images have a raw resolution of 5472x3648 pixels and a GSD of 0.27 cm per pixel. The inclusion of both ground and UAV images with different resolutions and GSDs provides a diverse range of data for training and evaluating object detection models for wheat head detection.&rft.creator=Mr Chris James&rft.creator=Mr Chris James&rft.creator=Professor Scott Chapman&rft.creator=Professor Scott Chapman&rft.date=2023&rft_rights= http://guides.library.uq.edu.au/deposit_your_data/terms_and_conditions&rft_subject=eng&rft_subject=RGB images&rft_subject=Unmanned Aerial Vehicle&rft_subject=Wheat head detection&rft_subject=Agricultural production systems simulation&rft_subject=Agriculture, land and farm management&rft_subject=AGRICULTURAL, VETERINARY AND FOOD SCIENCES&rft_subject=Agricultural spatial analysis and modelling&rft_subject=Crop and pasture improvement (incl. selection and breeding)&rft_subject=Crop and pasture production&rft.type=dataset&rft.language=English Access the data
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chris.james@uq.edu.au
School of Agriculture and Food Sciences

Full description

This dataset consists of RGB images captured during late harvest stage of wheat plots at the University of Queensland's Gatton campus in November 2021. The dataset is divided into three subsets: 2 sets of images acquired using a UAV (Unmanned Aerial Vehicle) and a set of images captured with a ground camera. Each subset includes bounding box annotations for training and evaluating object detection models. The ground images in this dataset were captured using the OpenCV OAK-1 camera, positioned at a height of approximately 1.5 meters above the canopy. These images have a raw resolution of 2160x2160 pixels and a Ground Sampling Distance (GSD) of approximately 0.030 cm per pixel. The UAV images were acquired using the DJI Phantom 4 Pro drone, flying at an altitude of 10 meters. These images have a raw resolution of 5472x3648 pixels and a GSD of 0.27 cm per pixel. The inclusion of both ground and UAV images with different resolutions and GSDs provides a diverse range of data for training and evaluating object detection models for wheat head detection.

Issued: 2023

Data time period: 2021 to 2021

Data time period: Data collected from: 2021-01-01T00:00:00Z
Data collected to: 2021-01-01T00:00:00Z

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Subjects
Agricultural, Veterinary and Food Sciences | Agricultural Production Systems Simulation | Agricultural Spatial Analysis and Modelling | Agriculture, Land and Farm Management | Crop and Pasture Improvement (Incl. Selection and Breeding) | Crop and Pasture Production | RGB images | Unmanned Aerial Vehicle | Wheat head detection | eng |

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local : UQ:289097

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local : UQ:06510ce

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