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Amazon Rekognition content moderation is a deep learning-based feature that can detect inappropriate, unwanted, or offensive images and videos, making it easier to find and remove such content at scale. Customers across industries, such as social media, gaming, and advertising, use Rekognition’s content moderation capabilities to protect their brand reputation, and enable safe user communities. With Custom Moderation, customers can now enhance the accuracy of the moderation deep learning model on their business-specific data by training an adapter with as few as twenty annotated images in less than hour. View the full article
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Amazon Rekognition Custom Labels is an automated machine learning (AutoML) feature that allows customers to find objects and scenes in images, unique to their business needs, with a simple inference API. Customers can create a custom ML model simply by uploading labeled images. No ML expertise is required. View the full article
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Amazon Rekognition Custom Labels is an automated machine learning (AutoML) feature that allows customers to find objects and scenes in images unique to their business needs with a simple inference API. Customers can create a custom ML model simply by uploading labeled images. No ML expertise is required. View the full article
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Amazon Rekognition is a deep-learning-based image and video analysis service that can identify objects, text, scenes, as well as support content moderation by detecting inappropriate content. Starting today, Amazon Rekognition can analyze images to detect if persons in the images are wearing Personal Protective Equipment (PPE) such as face covers (face masks), hand covers (gloves), and head covers (helmets or hard hats). View the full article
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