If you're like most companies, you wish to better understand your customers and your brand image. You'd like to track the success of your marketing campaigns, and the topics of interest--or frustration--for your customers. Social media promises to be a rich source of this kind of information, and many companies are beginning to collect, aggregate, and analyze the information from platforms like Twitter. However, more and more social media conversations center around images and video; on one recent project, approximately 30% of all tweets collected included one or more images. These images contain relevant information that is not readily accessible without analysis.
What to expect • Quick intro • 3 demo applications • Polly • Rekognition • MXnet • Wrap up. 4. 2017, Amazon Web Services, Inc. or its Affiliates. Event driven A B CEvent on B by A triggers C Invocation Lambda functions Action 6. 2017, Amazon Web Services, Inc. or its Affiliates. How Lambda works S3 event notifications DynamoDB Streams Kinesis events Cognito events SNS events Custom events CloudTrail events LambdaDynamoDB Kinesis S3 Any custom Invoked in response to events - Changes in data - Changes in state Redshift SNS Access any service, including your own Such as… Lambda functions CloudWatch events 7. 2017, Amazon Web Services, Inc. or its Affiliates. No servers to provision or manage Scales with usage Never pay for idle Availability and fault tolerance built in Serverless means… 9. 2017, Amazon Web Services, Inc. or its Affiliates. EVENT DRIVEN CONTINUOUS SCALING PAY BY USAGE Serverless means… 10. 2017, Amazon Web Services, Inc. or its Affiliates.
Amazon Rekognition is an AWS service that makes it easy to add image analysis to your applications. The latest feature added to the API for this deep-learning-powered computer vision is Celebrity Recognition. This simple-to-use functionality detects and recognizes thousands of individuals who are famous, noteworthy, or prominent in their field. Users can harness the tool to index and search digital image libraries for celebrities based on any particular interest. One common way we have seen our customers store data about individuals is within graph databases.
Amazon Rekognition is a service that makes it easy to add image analysis to your applications. It's based on the same proven, highly scalable, deep learning technology developed by Amazon's computer vision scientists to analyze billions of images daily for Amazon Prime Photos. Facial recognition enables you to find similar faces in a large collection of images. In this post, I'll show you how to build your own face recognition service by combining the capabilities of Amazon Rekognition and other AWS services, like Amazon DynamoDB and AWS Lambda. This enables you to build a solution to create, maintain, and query your own collections of faces, be it for the automated detection of people within an image library, building access control, or any other use case you can think of.
Imagine you work for a marketing agency that has tens of thousands of stock images. You find that many images don't have descriptive file names and others are completely mislabeled. You don't want to spend hours and hours relabeling them and moving them around to different folders. But what if you could find the images you need without relying on metadata? In this blog post, we will review an end-to-end solution to show you how to do this using Amazon Rekognition.