Artificial Intelligence
Computer vision in animal monitoring has become a research application in stable or confined conditions.
Detecting animals from the top view is challenging due to barn conditions.
In this dataset called ICV-TxLamb, images are proposed for the monitoring of lamb inside a barn.
This set of data is made up of two categories, the first is lamb (classifies the only lamb), the second consists of four states of the posture of lambs, these are: eating, sleeping, lying down, and normal (standing or without activity ).
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AI Ethics Global Document Collection Daniel Schiff, Jason Borenstein, Justin Biddle, & Kelly Laas Documents in the dataset were published between January 2016 through July 2019 This dataset is associated with a (forthcoming) paper in IEEE Transactions on Technology and Society, entitled "AI Ethics in the Public, Private, and NGO Sectors: A Review of a Global Document Collection.
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AI Ethics Global Document Collection
Daniel Schiff, Jason Borenstein, Justin Biddle, & Kelly Laas
Documents in the dataset were published between January 2016 through July 2019
This dataset is associated with a (forthcoming) paper in IEEE Transactions on Technology and Society, entitled "AI Ethics in the Public, Private, and NGO Sectors: A Review of a Global Document Collection.
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Wildfires are one of the deadliest and dangerous natural disasters in the world. Wildfires burn millions of forests and they put many lives of humans and animals in danger. Predicting fire behavior can help firefighters to have better fire management and scheduling for future incidents and also it reduces the life risks for the firefighters. Recent advance in aerial images shows that they can be beneficial in wildfire studies.
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The LGP dataset (LGPSSD) consists of LGP samples collected from the industrial site through the image acquisition device of LGP defect detection system. In our dataset, NG samples are regarded as positive samples, and OK samples are regarded as negative samples.
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This dataset has been created from a collection of 56403 multidisciplinary book titles from Springer, available through the Hellenic Academic Libraries Link (https://www.heal-link.gr/en/home-2/) subscription. To obtain this dataset, a parser was created for extracting relevant information, such as the title, subtitle and ToC, from each book. The extracted information was stored in a database for further processing. Each book title in the database includes information regarding the bookid, title, and ToC.
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This is a large Chinese taxonomic knowledge base, which is translated from Probase by the neural network.
It has 11,292,493 IsA pairs with an accuracy of 86.6%.
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Amidst the COVID-19 pandemic, cyberbullying has become an even more serious threat. Our work aims to investigate the viability of an automatic multiclass cyberbullying detection model that is able to classify whether a cyberbully is targeting a victim’s age, ethnicity, gender, religion, or other quality. Previous literature has not yet explored making fine-grained cyberbullying classifications of such magnitude, and existing cyberbullying datasets suffer from quite severe class imbalances.
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