Computer Vision is a field of artificial intelligence that seeks to understand digital images from cameras and videos by leveraging state of the art deep learning models. Business use cases of computer vision covers the entire gamut from defect detection of products in a manufacturing plant to identification of potentially malignant tumor in the human body, to traffic monitoring for smart city initiatives, and much more. These applications will continue to improve with faster processors, more advanced deep learning algorithms, and deeper integration to edge devices.
For computer vision to bring value to a business, it is important to focus not only on the development of deep learning models but also on the deployment of these models. In the Internet of Things (IoT) era, when large amounts of streaming data are generated continuously, it is extremely inefficient to store all these data in the cloud. For real-time image or video processing, moving the analytics to edge devices not only saves a device-to-cloud data round trip but also improves data privacy and governance.
SAS tackles the end-to-end lifecycle of a computer vision pipeline from model building to deployment in two phases:
Please take a look at this video to learn the details behind solving computer vision use cases using SAS.
Great video!
Awesome video - Love how you broke down a complex subject into simple digestible points.
Great video as usual Juthika!
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