Artificial Intelligence
The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. Early detection and diagnosis of ocular pathologies would enable forestall of visual impairment. One challenge that limits the adoption of computer-aided diagnosis tool by ophthalmologists is the number of sight-threatening rare pathologies, such as central retinal artery occlusion or anterior ischemic optic neuropathy, and others are usually ignored.
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This dataset contains 1944 data, which are scanned by the HIS-RING PACT system.
the data sampling rate of our system is 40 MSa/s, a 128-elements 2.5MHz full-view ring-shaped transducer with 30mm radius.
continuous updating.....
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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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