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Amazon Releases A New Tool To Improve Machine Learning Processes

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One of Amazon's most recent announcements was the release of their new tool called Amazon Rekognition Custom Labels. This advanced tool has the capability to improve machine learning on a whole new scale, allowing for better data analysis and object recognition. Amazon Rekognition will help users train their machine learning models more easily and allow them to understand a set of objects out of limited data. In other words, this capability will make machines more intelligent and capable of recognizing items with far less data sets than ever before. Employees stand near an The Amazon Inc. logo is displayed above the reception counter at the ... [ ] company's campus in Hyderabad, India, on Friday, Sept. 6, 2019.


Global Big Data Conference

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One of Amazon's most recent announcements was the release of their new tool called Amazon Rekognition Custom Labels. This advanced tool has the capability to improve machine learning on a whole new scale, allowing for better data analysis and object recognition. Amazon Rekognition will help users train their machine learning models more easily and allow them to understand a set of objects out of limited data. In other words, this capability will make machines more intelligent and capable of recognizing items with far less data sets than ever before. Machine learning includes a scientific study and adoption of algorithms that allow computers to learn new information and functionalities without needing direct instructions.


New Amazon tool helps machine learning models identify unique objects – TechCrunch

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Amazon announced a new capability today called Amazon Rekognition Custom Labels to help customers train machine learning models to understand a set of objects when there is a limited set of information. Typically, machine learning models have to work on large data sets to learn something like what's a picture of a dog, as opposed to some other animals. Amazon Rekognition Custom Labels can work with a limited data set to teach the algorithm a group of objects specific to a given use case. "Instead of having to train a model from scratch, which requires specialized machine learning expertise and millions of high-quality labeled images, customers can now use Amazon Rekognition Custom Labels to achieve state-of-the-art performance for their unique image analysis needs," the company wrote in a blog post announcing the new feature. For example, you may want to teach the model to identify a set of engine parts, a limited set of information, which has a lot of meaning to a specific use case.



Automatically detecting personal protective equipment on persons in images using Amazon Rekognition

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The following image shows an example input image and its corresponding output from the DetectProtectiveEquipment as seen on the Amazon Rekognition PPE detection console. In this example, we supply face cover as the required PPE and 80% as the required minimum confidence threshold as part of summarizationattributes. We receive a summarization result that indicates that there are four persons in the image that are wearing face covers at a confidence score of over 80% [person identifiers 0, 1,2, 3]. It also provides the full fidelity API response in the per-person results. Note that this feature doesn't perform facial recognition or facial comparison and can't identify the detected persons.