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Vision Checklist: Towards Testable Error Analysis of Image Models to Help System Designers Interrogate Model Capabilities. (arXiv:2201.11674v1 [cs.CV])
Jan. 28, 2022, 2:11 a.m. | Xin Du, Benedicte Legastelois, Bhargavi Ganesh, Ajitha Rajan, Hana Chockler, Vaishak Belle, Stuart Anderson, Subramanian Ramamoorthy
cs.LG updates on arXiv.org arxiv.org
Using large pre-trained models for image recognition tasks is becoming
increasingly common owing to the well acknowledged success of recent models
like vision transformers and other CNN-based models like VGG and Resnet. The
high accuracy of these models on benchmark tasks has translated into their
practical use across many domains including safety-critical applications like
autonomous driving and medical diagnostics. Despite their widespread use, image
models have been shown to be fragile to changes in the operating environment,
bringing their robustness …
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