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Okl AI homa @OKCompVision

Making products with AI. Oklahoma Joined March 2025
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Okl AI homa @OKCompVision

a year ago

@RubenAMtz Exactly! Sincle anomalies are by definition unique and rare, there should be few examples throughout the batch. This allows the use of one anomaly detection model in multiple domains.

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Okl AI homa @OKCompVision

a year ago

@RubenAMtz No reference images. Our architecture is based on the MuSc anomaly detection model. Features are extracted by a ViT, compared granularly using Local Neighborhood Aggregation with Multiple Degrees (LNAMD) and compared against eachother using Mutual Scoring Mechanism (MSM).

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Okl AI homa @OKCompVision

a year ago

We have implemented a new feature: soft memory. Our anomaly detection model performs inference in batches. By adding known normal samples to each batch, you can train the model in real time and reduce false positives. Videos coming soon!

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Okl AI homa @OKCompVision

a year ago

Unlike typical industrial models, zero shot models require no training and can be deployed and then "fine tuned" for near immediate results. #zeroshot #AI #DeepLearning #MachineLearning #Industry40 #ComputerVision

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Okl AI homa @OKCompVision

a year ago

Zero shot, zero training, minimal setup. With a camera in place, we can begin state-of-the-art anomaly detection anywhere. #AI #SOTA #ComputerVision #ZeroShot #NoTraining

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Okl AI homa @OKCompVision

a year ago

Zero-Shot Industrial Anomaly Detection in real time. Utilizing AI for robust quality control in industrial environments, with absolutely no training required. #IndustrialAI #ComputerVision #AI #Manufacturing #AnomalyDetection

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