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Whitepaper: 6 Challenges in Operationalizing CV Models

Download this comprehensive guide for measuring and improving computer vision models for accuracy, explainability, and bias. 

Arthur is the only AI Performance solution for computer vision models

Identify Anomalies & Data Drift

Automatic out-of-distribution detection lets you identify where your model is likely making mistakes.

Improve Models & Explore Datasets

Explore the results of your CV models (classification and object detection) with an interactive interface that makes it easy to identify issues.

Understand Your Models Better

Visualize important image regions that are impactful for model predictions.

Measure & Improve Accuracy, Explainability, and Fairness for Your CV Models

Accuracy & Data Drift

Monitor CV model pipelines for data anomalies using built-in out-of-distribution detection and track the accuracy of bounding box models

Explainability

Visualize which regions of an image are impactful for an image classification model’s decision or how your object detection models are performing on pipeline images

Bias Mitigation

Detect biases in your CV models by evaluating image classification outputs using an interactive interface and locating where your models misclassify and perpetuate bias

Our team has many models in production. With Arthur, checking their output and status at a glance is easy.

– Chris Poirier, VP of Data at Truebill

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