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Showing results for tags 'amazon lookout'.
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Amazon Lookout for Vision now provides anomaly localization through semantic segmentation. You can use Lookout for Vision’s segmentation models to identify the locations on an image where different types of anomalies (such as a scratch, dent, or tear) are present, the label of the anomaly and the size of the anomaly, which you can then use to make decisions such as classify, grade, bin product and ship, rework, or scrap the part. You can deploy the trained semantic segmentation models for inference in the AWS Cloud via the AWS SDK or CLI. You can also deploy them to an edge hardware device of your choice and run inference locally on the device. View the full article -
We are excited to announce that you can now add filters to alerts and also edit existing alerts while using Amazon Lookout for Metrics. With this launch you can now add filters to your alerts configuration to only get notifications for anomalies that matter the most to you. You can also simply modify existing alerts as per your needs for notification as anomalies evolve. View the full article
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Amazon Lookout for Vision is a new machine learning service that enables you to find visual defects in industrial products, accurately and at scale. With Lookout for Vision you can automate real-time visual inspection with computer vision for processes like quality control and defect assessment - with no machine learning expertise required. It uses computer vision to identify missing components in products, damage to vehicles or structures, irregularities in production lines, and even miniscule defects in silicon wafers — or any other physical item where quality is important. View the full article
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Today, we are excited to announce Amazon Lookout for Equipment, a service which provides customers with existing sensors on their industrial equipment, a way to send their sensor data to AWS to build machine learning models for them and return predictions to detect abnormal equipment behavior. This enables predictive maintenance that allows them to take action before machine failures occur and avoid unplanned downtime. View the full article
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