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Machine Learning Dataset for Poultry Diseases Diagnostics

Authors: Machuve, Dina; Nwankwo, Ezinne; Mduma, Neema; Mbelwa, Hope; Maguo, Evarist; Munisi, Charles;

Machine Learning Dataset for Poultry Diseases Diagnostics

Abstract

The annotated dataset of poultry diseases diagnostics for small to medium scale poultry farmers consists of poultry fecal images. The poultry fecal images were taken in Arusha and Kilimanjaro regions in Tanzania between September 2020 and December 2020 using Open Data Kit (ODK) app on mobile phones. The typical normal fecal material which is the ‘healthy’ class and Coccidiosis disease, the ‘cocci’ class were taken from poultry farms. The chickens were inoculated for Salmonella disease and fecal images taken from the diseased chickens for the ‘salmo’ class after one week. All images are in the .zip files; “cocci.zip” has 2103 images, “healthy.zip” has 2057 images, “salmo.zip” has 2276 images. A total of 6,436 image files are labeled. The “imgObjDet_Yolo.zip” and “imgSegmentation.zip” files consist of the corresponding annotations for object detection on YOLO framework and JSON files for semantic segmentation tasks respectively.

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Keywords

Poultry diseases, Coccidiosis, Salmonella, Deep learning, Newcastle disease

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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3
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