AWS Architecture Blog

Category: Amazon Rekognition

Figure 7. Fan out design pattern including secondary pipeline for deleting images

Get Started with Amazon S3 Event Driven Design Patterns

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 […]

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Figure 1 - Architecture Showing how to build an automated Image Processing and Model Training pipeline

Field Notes: Building an Automated Image Processing and Model Training Pipeline for Autonomous Driving

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 […]

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Figure 2. Solution overview diagram

Intelligently Search Media Assets with Amazon Rekognition and Amazon ES

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 […]

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Figure 1. Architecture for managing, anonymizing, and analyzing medical image data

Using AppStream 2.0 to Deliver PACS and Image Analysis in Clinical Trials

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 […]

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Figure 4. Discovering Hot Topics using Machine Learning solution architecture

Discovering Hot Topics using Machine Learning

Successful businesses not only have great products and services; they also have a deep understanding of their customers. Companies that can use behavioral analytics in marketing automation platforms are better equipped to deliver real-time marketing efforts. According to a research case study from Deloitte, companies with a customer-centric business model are 60% more profitable. Knowing […]

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Video Redaction - Multiprocessing

Field Notes: Speed Up Redaction of Connected Car Data by Multiprocessing Video Footage with Amazon Rekognition

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 […]

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SIH: Emvironment in AWS Cloud-2

Fast and Cost-Effective Image Manipulation with Serverless Image Handler

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 […]

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Video Redaction

Field Notes: Redacting Personal Data from Connected Cars Using Amazon Rekognition

Cameras mounted in connected cars may collect a variety of video data. Organizations may need to redact the personal information (e.g. human faces and automobile license plates) contained in the collected video data in order to protect individuals’ privacy rights and, where required, meet compliance obligations under privacy regulations such as General Data Protection Regulation […]

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