Investments in computer vision technology can help agribusinesses and food manufacturers of all types spot signs of trouble early and stop costly, potentially deadly recalls before they happen. Deployed across the production and manufacturing cycles, these models can detect hazards ranging from contaminants and foreign objects to defective equipment and non-compliant behavior. Organizations capture hundreds of thousands of hours of visual data in the form of video footage and imagery every day, and computer vision allows these businesses to put this data to work for process transformation.
Computer Vision
How Can Vision AI Predict and Prevent Supply Chain Disruptions?
Introducing computer vision across the supply chain can help manufacturers predict and prevent the types of conditions that lead to these kinds of disruptions. From potential contaminants and foreign objects to defective products and packaging to unsafe or unsanitary behavior, computer vision is the key to recognizing supply chain obstacles early and stopping shortages in their tracks. AI solutions could prove especially useful in volatile, high-production periods where errors and disruptions are both especially likely and especially costly.
Vision AI Is Seeing Manufacturers Into the Future
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
Using SmartML for Melanoma Segmentation with Dermoscopic Images
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.
SmartML: Train Vision AI Models with One Click
New Excerpt: SmartML is Plainsight’s proprietary model training toolset. It is at the heart of Plainsight’s proven approach to enterprise computer vision.
Computer Vision and Retail’s Digital Transformation
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.
Vision AI for Fighting and Preventing Wildfires
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.
Object Detection: An Introduction
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.
See More to Learn More and Solve More with Plainsight Vision AI
Visual data truly is the last great untapped resource for enterprises hoping to analyze and better understand their business. Without computer vision technology to derive insights from their images or video streams, organizations are unable to do much more than just collect visual data. AI-powered computer vision solutions offer the means to put visual data to work, improving processes and solving business challenges.
Computer Vision and Waste Recycling: Solving the Trash Problem
Happy Earth Day! Waste management might not be the first thing you think about when someone mentions computer vision but it’s actually an excellent use case for the technology.
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