AI Inspection: Machine Learning / Computer Vision for Visual Defect Detection
Watch how AI visual inspection operates. Learn more at https://mobidev.biz/blog/ai-visual-inspection-deep-learning-computer-vision-defect-detection
AI Visual defect inspection based on machine learning and computer vision techniques is used for the defect and mismatch assessment. It can be used in such industries as retail, manufacturing, airport baggage screening, the food industry, medicine, etc.
Let’s see how AI inspection works!
Recent progress in computer vision makes it possible to use advanced deep learning technologies for visual inspection. Images captured by a camera are processed by a neural network which is trained to detect and localize the defect. Once the visual inspection system is confident about where the problem is, it takes predefined actions, like sending a notification or executing other operations.
What are the possibilities of AI visual inspection for business?
Let’s imagine that we are producing sunflower oil. Even during production, bottles can be damaged that may result in additional costs and trouble during transportation. Thus, visual inspection based on the computer vision model detects the mismatch and notifies us in real-time so that defective objects can be excluded before they reach the final packaging stage.
Another example: different working areas on a plant requires workers to have certain equipment to be worn. Like helmets, gloves or boots. The neural network is able to analyze stream from monitoring cameras and notify if anyone working in the areas violates the requirements for this certain zone.
What is required for AI inspection implementation?
A correctly trained neural network ensures high accuracy of the quality management system. The network can be trained with many images of different objects. The network architecture depends on the task: Image Classification, Object Detection or Semantic Segmentation. Depending on how precisely we'd like to determine the defect or mismatch, we define the task and train network so as to detect any meaningful deviations from the “standard” appearance.
These technologies can be applied by our team in your own projects. Contact us for machine learning consulting services at https://mobidev.biz/services/machine-learning-consulting or info@mobidev.biz
Видео AI Inspection: Machine Learning / Computer Vision for Visual Defect Detection канала MobiDev
AI Visual defect inspection based on machine learning and computer vision techniques is used for the defect and mismatch assessment. It can be used in such industries as retail, manufacturing, airport baggage screening, the food industry, medicine, etc.
Let’s see how AI inspection works!
Recent progress in computer vision makes it possible to use advanced deep learning technologies for visual inspection. Images captured by a camera are processed by a neural network which is trained to detect and localize the defect. Once the visual inspection system is confident about where the problem is, it takes predefined actions, like sending a notification or executing other operations.
What are the possibilities of AI visual inspection for business?
Let’s imagine that we are producing sunflower oil. Even during production, bottles can be damaged that may result in additional costs and trouble during transportation. Thus, visual inspection based on the computer vision model detects the mismatch and notifies us in real-time so that defective objects can be excluded before they reach the final packaging stage.
Another example: different working areas on a plant requires workers to have certain equipment to be worn. Like helmets, gloves or boots. The neural network is able to analyze stream from monitoring cameras and notify if anyone working in the areas violates the requirements for this certain zone.
What is required for AI inspection implementation?
A correctly trained neural network ensures high accuracy of the quality management system. The network can be trained with many images of different objects. The network architecture depends on the task: Image Classification, Object Detection or Semantic Segmentation. Depending on how precisely we'd like to determine the defect or mismatch, we define the task and train network so as to detect any meaningful deviations from the “standard” appearance.
These technologies can be applied by our team in your own projects. Contact us for machine learning consulting services at https://mobidev.biz/services/machine-learning-consulting or info@mobidev.biz
Видео AI Inspection: Machine Learning / Computer Vision for Visual Defect Detection канала MobiDev
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