OCI Vision is an AI service for performing deep-learning–based image analysis at scale. With prebuilt models available out of the box, developers can easily build image recognition and text recognition into their applications without machine learning (ML) expertise. For industry-specific use cases, developers can automatically train custom vision models with their own data. These models can be used to detect visual anomalies in manufacturing, organize digital media assets, and tag items in images to count products or shipments.
Automatically extract textual or visual information from images and use that to power analytic applications. Combine visual information from images with additional inputs, such as product sales history and customer reviews to gain a holistic sense of trends, such as product availability and popularity.
Enrich image-based files with metadata, including objects and colors for better indexing and retrieval in a digital asset management system or larger data warehouse. Easily retrieve images for uses ranging from intelligent search to retail management.
Classify products or equipment as standard or defective based on visual appearance, such as discoloration, tear, rust, deformity, or breaks. Automate the detection of defective materials to flag the need for repairs.
Detect whether vegetation is growing in the surveillance image of a power line or if trucks are available at a lot for delivery by locating objects and entire scenes in images. Localize where particular objects are in a scene or classify the entire image.
Benjamin Arnulf, Senior Director, Product Strategy, Oracle Analytics
You can use OAC and OCI Vision together for many industry use cases. For example, you can see in this video how Children's Medical Research Institute can more quickly analyze microscope images and is significantly reducing their simulation time, increasing the speed at which they can drive progress. This blog describes some steps you can take to get the benefits of using OAC and OCI Vision in a low-code/no-code setting.
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