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Upleveling Image Segmentation with Segment Anything
Manage episode 409272195 series 3503604
Content provided by insight.tech. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by insight.tech or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Across all industries, businesses actively adopt computer vision to improve operations, elevate user experiences, and optimize overall efficiency. Image segmentation stands out as a key approach, enabling various applications such as recognition, localization, semantic understanding, augmented reality, and medical imaging. To make it easier to develop these types of applications, Meta AI released the Segment Anything Model (SAM)—an algorithm for identifying and segmenting any objects in an image without prior training.
In this podcast, we look at the evolution of image segmentation, what the launch of Meta AI’s Segment Anything model means to the computer vision community, and how developers can leverage OpenVINO™ to optimize for performance.
Join us as we explore these ideas with: Paula Ramos, AI Evangelist, Intel Christina Cardoza, Editorial Director, insight.tech
Paula answers our questions about
- The importance of image segmentation to computer vision
- Traditional challenges building image segmentation solutions
- What value the Segment Anything Model (SAM) brings
- Business opportunities for image segmentation and SAMs
- The power of OpenVINO to image segmentation
- The future of OpenVINO and Segment Anything
Related Content
To learn more about image segmentation, read Segment Anything Model — Versatile by Itself and Faster by OpenVINO. For the latest innovations from Intel, follow them on X at @IntelAI and on LinkedIn.
111 episodes
Share
Manage episode 409272195 series 3503604
Content provided by insight.tech. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by insight.tech or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Across all industries, businesses actively adopt computer vision to improve operations, elevate user experiences, and optimize overall efficiency. Image segmentation stands out as a key approach, enabling various applications such as recognition, localization, semantic understanding, augmented reality, and medical imaging. To make it easier to develop these types of applications, Meta AI released the Segment Anything Model (SAM)—an algorithm for identifying and segmenting any objects in an image without prior training.
In this podcast, we look at the evolution of image segmentation, what the launch of Meta AI’s Segment Anything model means to the computer vision community, and how developers can leverage OpenVINO™ to optimize for performance.
Join us as we explore these ideas with: Paula Ramos, AI Evangelist, Intel Christina Cardoza, Editorial Director, insight.tech
Paula answers our questions about
- The importance of image segmentation to computer vision
- Traditional challenges building image segmentation solutions
- What value the Segment Anything Model (SAM) brings
- Business opportunities for image segmentation and SAMs
- The power of OpenVINO to image segmentation
- The future of OpenVINO and Segment Anything
Related Content
To learn more about image segmentation, read Segment Anything Model — Versatile by Itself and Faster by OpenVINO. For the latest innovations from Intel, follow them on X at @IntelAI and on LinkedIn.
111 episodes
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Similar to InsightDotTech Talk
The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
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