AWS Machine Learning Blog
Category: Amazon Rekognition
Announcing Rekogniton Custom Moderation: Enhance accuracy of pre-trained Rekognition moderation models with your data
Companies increasingly rely on user-generated images and videos for engagement. From ecommerce platforms encouraging customers to share product images to social media companies promoting user-generated videos and images, using user content for engagement is a powerful strategy. However, it can be challenging to ensure that this user-generated content is consistent with your policies and fosters […]
Defect detection in high-resolution imagery using two-stage Amazon Rekognition Custom Labels models
High-resolution imagery is very prevalent in today’s world, from satellite imagery to drones and DLSR cameras. From this imagery, we can capture damage due to natural disasters, anomalies in manufacturing equipment, or very small defects such as defects on printed circuit boards (PCBs) or semiconductors. Building anomaly detection models using high-resolution imagery can be challenging […]
Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions
Purina US, a subsidiary of Nestlé, has a long history of enabling people to more easily adopt pets through Petfinder, a digital marketplace of over 11,000 animal shelters and rescue groups across the US, Canada, and Mexico. As the leading pet adoption platform, Petfinder has helped millions of pets find their forever homes. Purina consistently […]
Semantic image search for articles using Amazon Rekognition, Amazon SageMaker foundation models, and Amazon OpenSearch Service
Digital publishers are continuously looking for ways to streamline and automate their media workflows in order to generate and publish new content as rapidly as they can. Publishers can have repositories containing millions of images and in order to save money, they need to be able to reuse these images across articles. Finding the image that best matches an article in repositories of this scale can be a time-consuming, repetitive, manual task that can be automated. It also relies on the images in the repository being tagged correctly, which can also be automated (for a customer success story, refer to Aller Media Finds Success with KeyCore and AWS). In this post, we demonstrate how to use Amazon Rekognition, Amazon SageMaker JumpStart, and Amazon OpenSearch Service to solve this business problem.
Improving asset health and grid resilience using machine learning
Machine learning (ML) is transforming every industry, process, and business, but the path to success is not always straightforward. In this blog post, we demonstrate how Duke Energy, a Fortune 150 company headquartered in Charlotte, NC., collaborated with the AWS Machine Learning Solutions Lab (MLSL) to use computer vision to automate the inspection of wooden utility poles and help prevent power outages, property damage and even injuries.
How Amazon Shopping uses Amazon Rekognition Content Moderation to review harmful images in product reviews
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. These reviews have transformed into an essential source of information, enabling shoppers to access the opinions and experiences of other customers. As a […]
Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition
Computer vision (CV) is one of the most common applications of machine learning (ML) and deep learning. Use cases range from self-driving cars, content moderation on social media platforms, cancer detection, and automated defect detection. Amazon Rekognition is a fully managed service that can perform CV tasks like object detection, video segment detection, content moderation, […]
Safe image generation and diffusion models with Amazon AI content moderation services
Generative AI technology is improving rapidly, and it’s now possible to generate text and images based on text input. Stable Diffusion is a text-to-image model that empowers you to create photorealistic applications. You can easily generate images from text using Stable Diffusion models through Amazon SageMaker JumpStart. The following are examples of input texts and […]
Introducing an image-to-speech Generative AI application using Amazon SageMaker and Hugging Face
Vision loss comes in various forms. For some, it’s from birth, for others, it’s a slow descent over time which comes with many expiration dates: The day you can’t see pictures, recognize yourself, or loved ones faces or even read your mail. In our previous blogpost Enable the Visually Impaired to Hear Documents using Amazon […]
Build an image search engine with Amazon Kendra and Amazon Rekognition
In this post, we discuss a machine learning (ML) solution for complex image searches using Amazon Kendra and Amazon Rekognition. Specifically, we use the example of architecture diagrams for complex images due to their incorporation of numerous different visual icons and text. With the internet, searching and obtaining an image has never been easier. Most […]