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	<title>Amazon Rekognition &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/tag/amazon-rekognition/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Wed, 25 Oct 2023 18:52:03 +0000</lastBuildDate>
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		<title>Unstructured data management and governance using AWS AI/ML and analytics services</title>
		<link>https://noise.getoto.net/2023/10/25/unstructured-data-management-and-governance-using-aws-ai-ml-and-analytics-services/</link>
		
		<dc:creator><![CDATA[Sakti Mishra]]></dc:creator>
		<pubDate>Wed, 25 Oct 2023 18:52:03 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Comprehend]]></category>
		<category><![CDATA[Amazon DataZone]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Amazon Textract]]></category>
		<category><![CDATA[Amazon Transcribe]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<category><![CDATA[Thought Leadership]]></category>
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					<description><![CDATA[In this post, we discuss how AWS can help you successfully address the challenges of extracting insights from unstructured data. We discuss various design patterns and architectures for extracting and cataloging valuable insights from unstructured data using AWS. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.]]></description>
		
		
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			</item>
		<item>
		<title>AWS Week in Review: New Service for Generative AI and Amazon EC2 Trn1n, Inf2, and CodeWhisperer now GA – April 17, 2023</title>
		<link>https://noise.getoto.net/2023/04/17/aws-week-in-review-new-service-for-generative-ai-and-amazon-ec2-trn1n-inf2-and-codewhisperer-now-ga-april-17-2023/</link>
		
		<dc:creator><![CDATA[Antje Barth]]></dc:creator>
		<pubDate>Mon, 17 Apr 2023 19:12:09 +0000</pubDate>
				<category><![CDATA[.net]]></category>
		<category><![CDATA[Amazon CodeWhisperer]]></category>
		<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Amazon GameLift]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Inferentia]]></category>
		<category><![CDATA[AWS Well-Architected Framework]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[Week in Review]]></category>
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					<description><![CDATA[I could almost title this blog post the “AWS AI/ML Week in Review.” This past week, we announced several new innovations and tools for building with generative AI on AWS. Let’s dive right into it. Last Week’s Launches Here are some launches that got my attention during the previous week: Announcing Amazon Bedrock and Amazon […]]]></description>
		
		
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			</item>
		<item>
		<title>Detecting solar panel damage with Amazon Rekognition Custom Labels</title>
		<link>https://noise.getoto.net/2023/02/20/detecting-solar-panel-damage-with-amazon-rekognition-custom-labels/</link>
		
		<dc:creator><![CDATA[Ramakant Joshi]]></dc:creator>
		<pubDate>Mon, 20 Feb 2023 15:19:44 +0000</pubDate>
				<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Enterprises perform quality control to ensure products meet production standards and avoid potential brand reputation damage. As the cost of sensors decreases and connectivity increases, industries adopt real-time imagery analysis to detect quality issues. At the same time, artificial intelligence (AI) advancements enable advanced automation, reduce overall cost and project time, and produce accurate defect […]]]></description>
		
		
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			</item>
		<item>
		<title>Get Started with Amazon S3 Event Driven Design Patterns</title>
		<link>https://noise.getoto.net/2021/09/27/get-started-with-amazon-s3-event-driven-design-patterns/</link>
		
		<dc:creator><![CDATA[Micah Walter]]></dc:creator>
		<pubDate>Mon, 27 Sep 2021 15:38:56 +0000</pubDate>
				<category><![CDATA[A2P]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Simple Notification Service (SNS)]]></category>
		<category><![CDATA[Amazon Simple Queue Service (SQS)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=2a99eec7118cafd91ed83980d7ee8068</guid>

					<description><![CDATA[Event driven programs use events to initiate succeeding steps in a process. For example, the completion of an upload job may then initiate an image processing job. This allows developers to create complex architectures by using the principle of decoupling. Decoupling is preferable for many workflows, as it allows each component to perform its tasks […]]]></description>
		
		
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			</item>
		<item>
		<title>Creating a serverless face blurring service for photos in Amazon S3</title>
		<link>https://noise.getoto.net/2021/09/27/creating-a-serverless-face-blurring-service-for-photos-in-amazon-s3/</link>
		
		<dc:creator><![CDATA[James Beswick]]></dc:creator>
		<pubDate>Mon, 27 Sep 2021 14:40:09 +0000</pubDate>
				<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Simple Queue Service (SQS)]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[serverless]]></category>
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					<description><![CDATA[A serverless face blurring service can provide a simpler way to process photos in workloads with large amounts of traffic. This post introduces an example application that blurs faces when images are saved in an S3 bucket. The S3 PutObject event invokes a Lambda function that uses Amazon Rekognition to detect faces and GraphicsMagick to process the images.]]></description>
		
		
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			</item>
		<item>
		<title>Scaling Ad Verification with Machine Learning and AWS Inferentia</title>
		<link>https://noise.getoto.net/2021/09/22/scaling-ad-verification-with-machine-learning-and-aws-inferentia/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Wed, 22 Sep 2021 17:42:26 +0000</pubDate>
				<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Inferentia]]></category>
		<category><![CDATA[Thought Leadership]]></category>
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					<description><![CDATA[Amazon Advertising helps companies build their brand and connect with shoppers, through ads shown both within and beyond Amazon’s store, including websites, apps, and streaming TV content in more than 15 countries. Businesses or brands of all sizes including registered sellers, vendors, book vendors, Kindle Direct Publishing (KDP) authors, app developers, and agencies on Amazon […]]]></description>
		
		
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			</item>
		<item>
		<title>Field Notes: Building an Automated Image Processing and Model Training Pipeline for Autonomous Driving</title>
		<link>https://noise.getoto.net/2021/08/03/field-notes-building-an-automated-image-processing-and-model-training-pipeline-for-autonomous-driving/</link>
		
		<dc:creator><![CDATA[Antonia Schulze]]></dc:creator>
		<pubDate>Mon, 02 Aug 2021 22:58:54 +0000</pubDate>
				<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon SageMaker Ground Truth]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[Field Notes]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=e602db877d084b56075410c2e1ce88ee</guid>

					<description><![CDATA[In this blog post, we demonstrate how to build an automated and scalable data pipeline for autonomous driving. This solution was built with the goal of accelerating the process of analyzing recorded footage and training a model to improve the experience of autonomous driving. We will demonstrate the extraction of images from ROS bag file […]]]></description>
		
		
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			</item>
		<item>
		<title>Building a serverless multiplayer game that scales: Part 2</title>
		<link>https://noise.getoto.net/2021/07/29/building-a-serverless-multiplayer-game-that-scales-part-2/</link>
		
		<dc:creator><![CDATA[James Beswick]]></dc:creator>
		<pubDate>Thu, 29 Jul 2021 14:26:33 +0000</pubDate>
				<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Simple Storage Services (S3)]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<category><![CDATA[contributed]]></category>
		<category><![CDATA[serverless]]></category>
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					<description><![CDATA[This post shows how you can add scaling support for a game via automation. The example uses Amazon Rekognition to check images for unacceptable content and uses asynchronous architecture patterns with Step Functions and HTTP WebPush.]]></description>
		
		
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			</item>
		<item>
		<title>Intelligently Search Media Assets with Amazon Rekognition and Amazon ES</title>
		<link>https://noise.getoto.net/2021/07/14/intelligently-search-media-assets-with-amazon-rekognition-and-amazon-es/</link>
		
		<dc:creator><![CDATA[Sridhar Chevendra]]></dc:creator>
		<pubDate>Wed, 14 Jul 2021 16:03:34 +0000</pubDate>
				<category><![CDATA[Amazon Elasticsearch Service]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Simple Storage Services (S3)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=aa41cddb932662d5034b4a06f6b07239</guid>

					<description><![CDATA[Media assets have become increasingly important to industries like media and entertainment, manufacturing, education, social media applications, and retail. This is largely due to innovations in digital marketing, mobile, and ecommerce. Successfully locating a digital asset like a video, graphic, or image reduces costs related to reproducing or re-shooting. An efficient search engine is critical […]]]></description>
		
		
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		<item>
		<title>Using AppStream 2.0 to Deliver PACS and Image Analysis in Clinical Trials</title>
		<link>https://noise.getoto.net/2021/06/18/using-appstream-2-0-to-deliver-pacs-and-image-analysis-in-clinical-trials/</link>
		
		<dc:creator><![CDATA[Chris Fuller]]></dc:creator>
		<pubDate>Thu, 17 Jun 2021 23:11:00 +0000</pubDate>
				<category><![CDATA[Amazon AppStream 2.0]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Healthcare]]></category>
		<category><![CDATA[Life Sciences]]></category>
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					<description><![CDATA[Hospitals and clinical trial sites manage sensitive patient data. They are often required to grant remote access to custom Windows-based applications for patient record review and medical image analysis. This typically requires providing physicians and staff with remote access to on-premises workstations over VPN, with some flavor of remote desktop software. This can be both […]]]></description>
		
		
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		<item>
		<title>Field Notes: Speed Up Redaction of Connected Car Data by Multiprocessing Video Footage with Amazon Rekognition</title>
		<link>https://noise.getoto.net/2021/01/28/field-notes-speed-up-redaction-of-connected-car-data-by-multiprocessing-video-footage-with-amazon-rekognition/</link>
		
		<dc:creator><![CDATA[Sandeep Kulkarni]]></dc:creator>
		<pubDate>Thu, 28 Jan 2021 19:00:20 +0000</pubDate>
				<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[Field Notes]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=21cb292b7f3be2b673b5a5c55ad5d494</guid>

					<description><![CDATA[In the blog, Redacting Personal Data from Connected Cars Using Amazon Rekognition, we demonstrated how you can redact personal data such as human faces using Amazon Rekognition. Traversing the video, frame by frame, and identifying personal information in each frame takes time. This solution is great for small video clips, where you do not need […]]]></description>
		
		
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		<item>
		<title>Fast and Cost-Effective Image Manipulation with Serverless Image Handler</title>
		<link>https://noise.getoto.net/2020/11/23/fast-and-cost-effective-image-manipulation-with-serverless-image-handler/</link>
		
		<dc:creator><![CDATA[Ajay Swamy]]></dc:creator>
		<pubDate>Mon, 23 Nov 2020 16:48:59 +0000</pubDate>
				<category><![CDATA[Amazon API Gateway]]></category>
		<category><![CDATA[Amazon CloudFront]]></category>
		<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Simple Storage Services (S3)]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[AWS CloudFormation]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Secrets Manager]]></category>
		<category><![CDATA[aws solutions]]></category>
		<category><![CDATA[Serverless Image Handler]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=adabe9521f4378160dccde3d64a4d2fe</guid>

					<description><![CDATA[As a modern company, you most likely have both a web-based and mobile app platform to provide content to customers who view it on a range of devices. This means you need to store multiple versions of images, depending on the device. The resulting image management can be a headache as it can be expensive [&#8230;]]]></description>
		
		
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		<item>
		<title>Using serverless backends to iterate quickly on web apps – part 3</title>
		<link>https://noise.getoto.net/2020/08/31/using-serverless-backends-to-iterate-quickly-on-web-apps-part-3/</link>
		
		<dc:creator><![CDATA[James Beswick]]></dc:creator>
		<pubDate>Mon, 31 Aug 2020 14:23:17 +0000</pubDate>
				<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Serverless Application Model]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[Tutorial]]></category>
		<category><![CDATA[Vue.js]]></category>
		<category><![CDATA[Web app]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=9d0a7536c76eff49a3d817f5d9b7112e</guid>

					<description><![CDATA[Previously in this series, you deploy a simple workflow for processing image uploads in the Happy Path web application. In this post, you add progressively more complex functionality by deploying new versions of workflows.]]></description>
		
		
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