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What is Vision AI, and why is it important?
In this post, we’ll define vision AI, what it means for different businesses and stakeholders, and how any user can get started executing their computer vision project today.
5 Ways Agribusinesses Can Prevent Recalls, Shutdowns, and Delays with Vision AI
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.
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.
Autonomous Vehicles Are Driving Computer Vision Into the Future
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.
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.
Vision AI Use Cases for the Energy Sector: Monitor Storage Tanks & Detect VOC Leaks
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.
SmartML: Train Vision AI Models with One Click
SmartML is Plainsight’s proprietary model training toolset. It is at the heart of Plainsight’s promise to make vision AI’s impressive capabilities more accessible to users of all experience levels and enterprises of all types. Thanks to SmartML, Plainsight users can use their labeled datasets to train vision AI models without the need for a single line of code.
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