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Towards Total Recall in Industrial Anomaly Detection. (arXiv:2106.08265v2 [cs.CV] UPDATED)
Web: http://arxiv.org/abs/2106.08265
May 9, 2022, 1:10 a.m. | Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter Gehler
cs.CV updates on arXiv.org arxiv.org
Being able to spot defective parts is a critical component in large-scale
industrial manufacturing. A particular challenge that we address in this work
is the cold-start problem: fit a model using nominal (non-defective) example
images only. While handcrafted solutions per class are possible, the goal is to
build systems that work well simultaneously on many different tasks
automatically. The best performing approaches combine embeddings from ImageNet
models with an outlier detection model. In this paper, we extend on this line …
More from arxiv.org / cs.CV updates on arXiv.org
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