AWS Machine Learning Blog

Category: Amazon Rekognition

Automate annotation of image training data with Amazon Rekognition

Every machine learning (ML) model demands data to train it. If your model isn’t predicting Titanic survival or iris species, then acquiring a dataset might be one of the most time-consuming parts of your model-building process—second only to data cleaning. What data cleaning looks like varies from dataset to dataset. For example, the following is […]

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TC Energy builds an intelligent document processing workflow to process over 20 million images with Amazon AI

This is a guest post authored by Paul Ngo, US Gas Technical and Operational Services Data Team Lead at TC Energy. TC Energy operates a network of pipelines, including 57,900 miles of natural gas and 3,000 miles of oil and liquid pipelines, throughout North America. TC Energy enables a stable network of natural gas and […]

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Simplify data annotation and model training tasks with Amazon Rekognition Custom Labels

For a supervised machine learning (ML) problem, labels are values expected to be learned and predicted by a model. To obtain accurate labels, ML practitioners can either record them in real time or conduct offline data annotation, which are activities that assign labels to the dataset based on human intelligence. However, manual dataset annotation can […]

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Automate continuous model improvement with Amazon Rekognition Custom Labels and Amazon A2I: Part 2

In Part 1 of this series, we walk through a continuous model improvement machine learning (ML) workflow with Amazon Rekognition Custom Labels and Amazon Augmented AI (Amazon A2I). We explained how we use AWS Step Functions to orchestrate model training and deployment, and custom label detection backed by a human labeling private workforce. We described […]

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Automate continuous model improvement with Amazon Rekognition Custom Labels and Amazon A2I: Part 1

If you need to integrate image analysis into your business process to detect objects or scenes unique to your business domain, you need to build your own custom machine learning (ML) model. Building a custom model requires advanced ML expertise and can be a technical challenge if you have limited ML knowledge. Because model performance […]

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Defect detection and classification in manufacturing using Amazon Lookout for Vision and Amazon Rekognition Custom Labels

Defect detection during manufacturing processes is a vital step to ensure product quality. The timely detection of faults or defects and taking appropriate actions are essential to reduce operational and quality-related costs. According to Aberdeen’s research, “Many organizations will have true quality-related costs as high as 15 to 20 percent of sales revenue.” The current […]

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Optimize workforce in your store using Amazon Rekognition

In this post, we show you how to use Amazon Rekognition and AWS DeepLens to detect, and analyze occupancy in a retail business to optimize workforce utilization. Retailers often need to make decisions to improve the in-store customer experience through personnel management. Having too few or too many employees working can be detrimental to the […]

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Automate car insurance claims processing with Autonet and Amazon Rekognition Custom Labels

There is nothing more exhilarating than getting the keys to your first car or driving off the lot with the car of your dreams. Sadly, that exhilaration can quickly fade to frustration when your car is damaged. Working through the phone calls, emails, and damage reports with your insurance provider can be a painstaking process. […]

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Build an Automatic Inventory Solution with public datasets and Amazon Rekognition Custom Labels

Inventorying store items is a general demand for retail stores and supermarkets. This is usually performed manually by counting items and visually checking the correct placement. Tracking changes in inventory helps business owners evaluate performance of each product, validate correct placement, and set future restocking plans. With the cloud making AI and machine learning (ML) […]

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Automate weed detection in farm crops using Amazon Rekognition Custom Labels

Amazon Rekognition Custom Labels makes automated weed detection in crops easier. Instead of manually locating weeds, you can automate the process with Amazon Rekognition Custom Labels, which allows you to build machine learning (ML) models that can be trained with only a handful of images and yet are capable of accurately predicting which areas of […]

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