Makerere University Maize Image Dataset
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The dataset was created to provide an open and accessible maize dataset with well-labeled, sufficiently curated, and prepared maize crop imagery that will be used by data scientists, researchers, the wider machine learning community, and social entrepreneurs within Sub-saharan Africa and worldwide for various machine learning experiments so as to build solutions towards infield maize crop disease diagnosis and spatial analysis. The image dataset was collected across three different classes: Healthy, Maize Streak Virus (MSV), and Maize Leaf Blight (MLB)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Maize"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The dataset was created to provide an open and accessible maize dataset with well-labeled, sufficiently curated, and prepared maize crop imagery that will be used by data scientists, researchers, the wider machine learning community, and social entrepreneurs within Sub-saharan Africa and worldwide for various machine learning experiments so as to build solutions towards infield maize crop disease diagnosis and spatial analysis. The image dataset was collected across three different classes: Healthy, Maize Streak Virus (MSV), and Maize Leaf Blight (MLB)' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The dataset was created to provide an open and accessible maize dataset with well-labeled, sufficiently curated, and prepared maize crop imagery that will be used by data scientists, researchers, the wider machine learning community, and social entrepreneurs within Sub-saharan Africa and worldwide for various machine learning experiments so as to build solutions towards infield maize crop disease diagnosis and spatial analysis. The image dataset was collected across three different classes: Healthy, Maize Streak Virus (MSV), and Maize Leaf Blight (MLB)
Maize