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Part 1: Document Description
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Citation |
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Title: |
Dataset of Crops part one |
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Identification Number: |
doi:10.7910/DVN/J0OS9R |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2024-01-03 |
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Version: |
1 |
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Bibliographic Citation: |
Murindanyi, Sudi, 2024, "Dataset of Crops part one", https://doi.org/10.7910/DVN/J0OS9R, Harvard Dataverse, V1 |
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Citation |
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Title: |
Dataset of Crops part one |
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Identification Number: |
doi:10.7910/DVN/J0OS9R |
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Authoring Entity: |
Murindanyi, Sudi (Makerere University) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Murindanyi, Sudi |
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Depositor: |
Murindanyi, Sudi |
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Date of Deposit: |
2023-12-06 |
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Holdings Information: |
https://doi.org/10.7910/DVN/J0OS9R |
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Study Scope |
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Keywords: |
Agricultural Sciences |
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Abstract: |
This dataset consists of five classes of data in the training set: cassava, sugarcane, maize, cashew, and coffee images. This is the first part, which consists of five out of seven classes used in crop classification projects; train data, weeds, and unknown images are in the second part of this data, which also has validation data and test data. Additionally, when combining this data with its second part, they were prepared for classification, and they have three splits: train, validation, and test, with the data in the train set being augmented. There are 4074 images across all seven classes, with 582 images for each class, this is true when the both data are combined. Various methods were used to collect the data, including recording videos from the infield garden and extracting images and high-resolution images collected using drones in partnership with Makerere AI Lab, Uganda Marconi Lab, National Coffee Research Institute, and National Crops Resources Research Institute. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Label: |
train_cashew_cassava_coffe_maize_sugarcane.zip |
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Notes: |
application/zip |