AWS Machine Learning Blog
Category: Customer Enablement
Build a scalable machine learning pipeline for ultra-high resolution medical images using Amazon SageMaker
Neural networks have proven effective at solving complex computer vision tasks such as object detection, image similarity, and classification. With the evolution of low-cost GPUs, the computational cost of building and deploying a neural network has drastically reduced. However, most techniques are designed to handle pixel resolutions commonly found in visual media. For example, typical […]
Improve the streaming transcription experience with Amazon Transcribe partial results stabilization
Whether you’re watching a live broadcast of your favorite soccer team, having a video chat with a vendor, or calling your bank about a loan payment, streaming speech content is everywhere. You can apply a streaming transcription service to generate subtitles for content understanding and accessibility, to create metadata to enable search, or to extract […]
Automate multi-modality, parallel data labeling workflows with Amazon SageMaker Ground Truth and AWS Step Functions
This is the first in a two-part series on the Amazon SageMaker Ground Truth hierarchical labeling workflow and dashboards. In Part 1, we look at creating multi-step labeling workflows for hierarchical label taxonomies using AWS Step Functions. In Part 2 (coming soon), we look at how to build dashboards for analyzing dataset annotations and worker […]
Annotate dense point cloud data using Amazon SageMaker Ground Truth
Autonomous vehicle companies typically use LiDAR sensors to generate a 3D understanding of the environment around their vehicles. For example, they mount a LiDAR sensor on their vehicles to continuously capture point-in-time snapshots of the surrounding 3D environment. The LiDAR sensor output is a sequence of 3D point cloud frames (the typical capture rate is […]
Quality Assessment for SageMaker Ground Truth Video Object Tracking Annotations using Statistical Analysis
Data quality is an important topic for virtually all teams and systems deriving insights from data, especially teams and systems using machine learning (ML) models. Supervised ML is the task of learning a function that maps an input to an output based on examples of input-output pairs. For a supervised ML algorithm to effectively learn […]
HawkEye 360 uses Amazon SageMaker Autopilot to streamline machine learning model development for maritime vessel risk assessment
This post is cowritten by Ian Avilez and Tim Pavlick from HawkEye 360. HawkEye 360 is a commercial radio frequency (RF) satellite constellation data analytics provider. Our signals of interest include very high frequency (VHF) push-to-talk radios, maritime radar systems, AIS beacons, satellite mobile comms, and more. Our Mission Space offering, released in February 2021, […]
Protecting people from hazardous areas through virtual boundaries with Computer Vision
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. As companies welcome more autonomous robots and other heavy […]
Acoustic anomaly detection using Amazon Lookout for Equipment
As the modern factory becomes more connected, manufacturers are increasingly using a range of inputs (such as process data, audio, and visual) to increase their operational efficiency. Companies use this information to monitor equipment performance and anticipate failures using predictive maintenance techniques powered by machine learning (ML) and artificial intelligence (AI). Although traditional sensors built […]
Object detection with Detectron2 on Amazon SageMaker
Deep learning is at the forefront of most machine learning (ML) implementations across a broad set of business verticals. Driven by the highly flexible nature of neural networks, the boundary of what is possible has been pushed to a point where neural networks can outperform humans in a variety of tasks, such as object detection […]
PDF document pre-processing with Amazon Textract: Visuals detection and removal
Amazon Textract is a fully managed machine learning (ML) service that automatically extracts printed text, handwriting, and other data from scanned documents that goes beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables. Amazon Textract can detect text in a variety of documents, including financial reports, medical records, […]