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Once the stuff of science fiction, self-driving vehicles are now merging onto roadways and into the news. Organizations ranging from car manufacturers to rideshare services to restaurants have launched ambitious initiatives and even started testing autonomous vehicles on select public roads.
For many, the thought of advanced manufacturing processes conjures images of technology designed to mimic the human arm, safely assembling and handling products. However, some of the most exciting recent developments in the manufacturing space have to do with tech that mimics sight rather than touch. Rapid advancements in computer vision technology are transforming manufacturing by enabling organizations to derive powerful insights from their visual data
In a recent skin cancer research study, Dr. Bülent Bayram and his team at Yildiz Technical University, Department of Geomatics in Istanbul, Turkey, used Plainsight’s vision AI platform to perform image segmentation for early detection and analysis of skin cancer.
Energy providers have not only taken action to address the causes of leaks, but set ambitious goals to eliminate or offset their emissions altogether. The sector has undoubtedly grown both safer and more sustainable in the years since the above EPA statistics were first published. Still, without the added capabilities of vision AI-enhanced processes, they’re potentially missing opportunities for improvement and letting issues like leaks go undetected.
New Excerpt: SmartML is Plainsight’s proprietary model training toolset. It is at the heart of Plainsight’s proven approach to enterprise computer vision.
TrackForward is a Plainsight AI-powered labeling feature that can dramatically reduce the time and effort required for labeling video data. Using AI, TrackForward analyzes the labels in one frame of a video to predictively label objects in subsequent frames. By labeling an object with either a Bounding Box or Polygon and selecting the TrackForward tool, Plainsight users can quickly generate labels automatically for desired objects across entire videos.
When it comes to digital transformation, retailers are no longer asking, “What if?” They’re saying the time is now. For the retail industry in particular, integrating vision AI applications into traditional store operations can open up a world of fresh insights that empower better decision making.
In a recent skin cancer research study, Dr. Bülent Bayram and his team at Yildiz Technical University, Department of Geomatics in Istanbul, Turkey, used our vision AI platform to perform image segmentation for early detection and analysis of skin cancer.
By enhancing their computer vision technology and applying AI to visual data like satellite imagery and drone feeds, public and private sector organizations can better recognize wildfire risks, predict the likely path of blazes, and coordinate their fire-fighting efforts to protect communities.
Spotting relevant information in an image or video feed can feel a little like looking for a needle in a haystack, but it doesn’t have to require so much time and effort. Training AI to detect objects can help by streamlining and automating the process of generating insights from visual data.
May 9, 2023 | Press
May 8,2023 | Press
May 2,2023 | Blog
