Remove Amazon Rekognition Custom Labels
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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning

This post details how Purina used Amazon Rekognition Custom Labels , AWS Step Functions , and other AWS Services to create an ML model that detects the pet breed from an uploaded image and then uses the prediction to auto-populate the pet attributes.

APIs 95
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Automate Amazon Rekognition Custom Labels model training and deployment using AWS Step Functions

AWS Machine Learning

With Amazon Rekognition Custom Labels , you can have Amazon Rekognition train a custom model for object detection or image classification specific to your business needs. Generating this data can take months to gather and require large teams of labelers to prepare it for use in machine learning (ML).

APIs 80
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Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

AWS Machine Learning

Amazon Rekognition is a fully managed service that can perform CV tasks like object detection, video segment detection, content moderation, and more to extract insights from data without the need of any prior ML experience. In some cases, a more custom solution might be needed along with the service to solve a very specific problem.

APIs 63
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Analyze and tag assets stored in Veeva Vault PromoMats using Amazon AppFlow and Amazon AI Services

AWS Machine Learning

In a previous post , we talked about analyzing and tagging assets stored in Veeva Vault PromoMats using Amazon AI services and the Veeva Vault Platform’s APIs. The Amazon AppFlow Veeva connector is the first Amazon AppFlow connector supporting automatic transfer of Veeva documents.

APIs 73
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How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

AWS Machine Learning

Building enhanced semantic search capabilities that analyze media contextually would lay the groundwork for creating AI-generated content, allowing customers to produce customized media more efficiently. The videos from Amazon S3 are retrieved and converted to H264 vcodec format using the FFmpeg library.

APIs 98
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Easily build semantic image search using Amazon Titan

AWS Machine Learning

The previous post discussed how you can use Amazon machine learning (ML) services to help you find the best images to be placed along an article or TV synopsis without typing in keywords. In the previous post, you used Amazon Rekognition to extract metadata from an image. A key concept in semantic search is embeddings.

Scripts 94
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How Amazon Shopping uses Amazon Rekognition Content Moderation to review harmful images in product reviews

AWS Machine Learning

Customers are increasingly turning to product reviews to make informed decisions in their shopping journey, whether they’re purchasing everyday items like a kitchen towel or making major purchases like buying a car. Amazon has one of the largest stores with hundreds of millions of items available.

APIs 77