AWS Machine Learning Blog

Category: Amazon Rekognition

Scan Amazon S3 buckets for content moderation using S3 Batch and Amazon Rekognition

Dealing with content in large scale is often challenging, costly, and a heavy lift operation. The volume of user-generated and third-party content has been increasing substantially in industries like social media, ecommerce, online advertising, and media sharing. Customers may want to review this content to ensure that it follows corporate governance and regulations. But they […]

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Build your own brand detection and visibility using Amazon SageMaker Ground Truth and Amazon Rekognition Custom Labels – Part 2: Training and analysis workflows

In Part 1 of this series, we showed how to build a brand detection solution using Amazon SageMaker Ground Truth and Amazon Rekognition Custom Labels. The solution was built on a serverless architecture with a custom user interface to identify a company brand or logo from video content and get an in-depth view of screen […]

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Explore image analysis results from Amazon Rekognition and store your findings in Amazon DocumentDB

When we analyze images, we may want to incorporate other metadata related to the image. Examples include when and where the image was taken, who took the image, as well as what is featured in the image. One way to represent this metadata is to use a JSON format, which is well-suited for a document […]

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Calculate inference units for an Amazon Rekognition Custom Labels model

Amazon Rekognition Custom Labels allows you to extend the object and scene detection capabilities of Amazon Rekognition to extract information from images that is uniquely helpful to your business. For example, you can find your logo in social media posts, identify your products on store shelves, classify machine parts in an assembly line, distinguish healthy […]

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Enable scalable, highly accurate, and cost-effective video analytics with Axis Communications and Amazon Rekognition

With the number of cameras and sensors deployed growing exponentially, companies across industries are consuming more video than ever before. Additionally, advancements in analytics have expanded potential use cases, and these devices are now used to improve business operations and intelligence. In turn, the ability to effectively process video at these rapidly expanding volumes is […]

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Recognize celebrities in images and videos using Amazon Rekognition

The celebrity recognition feature in Amazon Rekognition automatically recognizes tens of thousands of well-known personalities in images and videos using machine learning (ML). Celebrity recognition significantly reduces the repetitive manual effort required to tag produced media content and make it readily searchable. Starting today, we’re updating our models to provide higher accuracy (lower false detections […]

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Detect small shapes and objects within your images using Amazon Rekognition Custom Labels

There are multiple scenarios in which you may want to use computer vision to detect small objects or symbols within a given image. Whether it’s detecting company logos on grocery store shelves to manage inventory, detecting informative symbols on documents, or evaluating survey or quiz documents that contain checkmarks or shaded circles, the size ratio […]

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Automate annotation of image training data with Amazon Rekognition

Every machine learning (ML) model demands data to train it. If your model isn’t predicting Titanic survival or iris species, then acquiring a dataset might be one of the most time-consuming parts of your model-building process—second only to data cleaning. What data cleaning looks like varies from dataset to dataset. For example, the following is […]

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TC Energy builds an intelligent document processing workflow to process over 20 million images with Amazon AI

This is a guest post authored by Paul Ngo, US Gas Technical and Operational Services Data Team Lead at TC Energy. TC Energy operates a network of pipelines, including 57,900 miles of natural gas and 3,000 miles of oil and liquid pipelines, throughout North America. TC Energy enables a stable network of natural gas and […]

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Simplify data annotation and model training tasks with Amazon Rekognition Custom Labels

For a supervised machine learning (ML) problem, labels are values expected to be learned and predicted by a model. To obtain accurate labels, ML practitioners can either record them in real time or conduct offline data annotation, which are activities that assign labels to the dataset based on human intelligence. However, manual dataset annotation can […]

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