AWS Machine Learning Blog
Category: Amazon Rekognition
Making daily dinner easy with Deliveroo meals and Amazon Rekognition
When Software Engineer Florian Thomas describes Deliveroo, he is talking about a rapidly growing, highly in-demand company. Everyone must eat, after all, and Deliveroo is, in his words, “on a mission to transform the way you order food.” Specifically, Deliveroo’s business is partnering with restaurants to bring customers their favorite eats, right to their doorsteps. […]
Capturing memories: GeoSnapShot uses Amazon Rekognition to identify athletes
If you’ve ever competed in a sporting event and painstakingly sifted through event photos to find yourself later, you’ll appreciate GeoSnapShot’s innovative solution powered by Amazon Rekognition. GeoSnapShot founder Andy Edwards was first introduced to the world of sports photography when he started accompanying his wife, a competitive equestrian, to her riding events and photographing […]
De-identify medical images with the help of Amazon Comprehend Medical and Amazon Rekognition
Medical images are a foundational tool in modern medicine that enable clinicians to visualize critical information about a patient to help diagnose and treat them. The digitization of medical images has vastly improved our ability to reliably store, share, view, search, and curate these images to assist our medical professionals. The number of modalities for […]
Amazon Rekognition announces updates to its face detection, analysis, and recognition capabilities
Today we are announcing updates to our face detection, analysis, and recognition features. These updates provide customers with improvements in the ability to detect more faces from images, perform higher accuracy face matches, and obtain improved age, gender, and emotion attributes for faces in images. Amazon Rekognition customers can use each of these enhancements starting […]
Track the number of coffees consumed using AWS DeepLens
April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. AWS DeepLens is a deep-learning-enabled video camera for developers. It […]
Shopper Sentiment: Analyzing in-store customer experience
Retailers have been using in-store video to analyze customer behaviors and demographics for many years. Separate systems are commonly used for different tasks. For example, one system would count the number of customers moving through a store, in which part of the store those customers linger and near which products. Another system will hold the store layout, whilst yet […]
New Engen improves customer acquisition marketing campaigns using Amazon Rekognition
New Engen is a cross-channel performance marketing technology company that uses its proprietary software products and creative solutions to help their clients acquire new customers. New Engen integrates marketing, AI, and creative expertise to provide a one-stop solution that helps their customers optimize their digital marketing budget across Facebook, Google, Instagram, Snap, and more. Improving […]
Save time and money by filtering faces during indexing with Amazon Rekognition
Amazon Rekognition is a deep-learning-based image and video analysis service that can identify objects, people, text, scenes, and activities, as well as detect any inappropriate content. Using the new Amazon Rekognition face filtering feature, you can now have control over the quality and quantity of faces you can index for face recognition. This saves on […]
Mapillary uses Amazon Rekognition to work towards building parking solutions for US cities
Mapillary is a collaborative street-level imagery platform that allows people and organizations to upload geo-tagged photos, which can then be used by customers to improve their mapping systems or applications. Mapillary uses Amazon Rekognition, a deep learning-based image and video analysis service, to enhance their metadata extraction. By using the DetectText operation from Amazon Rekognition, […]
Get started with automated metadata extraction using the AWS Media Analysis Solution
You can easily get started extracting meaningful metadata from your media files by using the Media Analysis Solution on AWS. The Media Analysis Solution provides AWS CloudFormation templates that you can use to start extracting meaningful metadata from your media files within minutes. With a web-based user interface, you can easily upload files and see the metadata that is automatically extracted. This solution uses Amazon Rekognition for facial recognition, Amazon Transcribe to create a transcript, and Amazon Comprehend to run sentiment analysis on the transcript. You can also upload your own images to an Amazon Rekognition collection and train the solution to recognize individuals. In this blog post, we’ll show you step-by step how to launch the solution and upload an image and video. You’ll be able to see firsthand how metadata is seamlessly extracted.