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AI Use Case

Predict potential quality issues with products through visual recognition

Use technologies, such as machine vision, to better detect quality control issues during key processes - vegetable sortign for quality for example. This will potentially help generate a better understanding of which internal processes, workflows and factor contribute most and least to meeting quality objectives.



Production Ip


Cost - Reduce wastage,Revenue - Product optimisation

Case Studies

"Kewpie~Kewpie, a Japanese food manufacturing company, used deep machine vision that identified defective potato cubes on the production line with the same level as accuracy as humans",Automotive Parts Manufacturer [unnamed]~Global manufacturer achieves more than 85% shorter inspection times and real time production feedback using deep learning algorithms for 100% automatic inspection ,Jabil~Jabil eliminates false-positives with automated optical inspection of its manufacturing processes using deep neural networks

Potential Vendors

Scortex,Microsoft Azure


Data Sets

Images,Time series

AI Technologies

Product Type - Vision ,Model Architecture - Convolutional Neural Network (CNN),Machine Learning (ML),Product Type - Vision - Object detection,Product Type - Vision - Object tracking,Product Type - Vision - Semantic segmentation,Product Type - Vision - Instance segmentatiuon,Product Type - Vision - Image classification

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