How to Operationalize & Scale Pipelines with Computer Vision Models at the Edge

Presented by

Sanjeev Heda, Principal Industry Consultant, SAS

About this talk

Many industries are turning to cameras and computer vision to solve novel and non-traditional challenges that may be hard to accomplish with traditional data sets. Example use-cases include biomedical imaging in Healthcare, smart cities for governments, and automated defect detection in manufacturing. However, just having a computer vision model is not enough to generate the necessary insight to drive action. There is a need to have a complete analytic pipeline that has all the necessary components to transform input data sets into actionable insights. This analytic pipeline must have sufficient accuracy to have confidence in predictions, minimal latency to provide these decisions in a timely manner, and have the ability to deploy and scale to multiple cameras and locations. Come and see how this analytic pipeline for a manufacturing use-case can be built and operationalized using the SAS Platform. We will show how the analytic pipeline consumes multiple data sources, contains multiple post-processing analytic techniques to interpret and generate actionable information from the computer vision model outputs, leveraging technology optimized for compute, and the intermixing of both SAS and Open Source technology in the same analytic pipeline.

Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (6)
Subscribers (2184)
In today's organizations, you need to get relevant data quickly to drive faster business decisions. With big data, sometimes that's easier said than done. SAS® Business Intelligence offers predictive insights with the ability to understand the past, monitor the present and predict outcomes, no matter the size or complexity of your data. In fact, SAS helps you deliver accurate, valuable information – from Hadoop or any other big data source. Plus, SAS offers an integrated, flexible presentation layer for the full breadth of SAS Analytics capabilities: data and text mining, statistics, predictive analytics, forecasting and optimization. One of the key components of SAS Business Intelligence, SAS Visual Analytics, offers self-service data discovery, enabling even nontechnical business users to explore billions of rows of data in seconds. With this tool, you can discover more opportunities and make more precise decisions, easily publishing reports to the Web and mobile devices.