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Pyramidal Image Anomaly Detector

A neural network for image anomaly detection with deep pyramidal reporesentations and dynamic routing

Pankaj Mishra, Claudio Piciarelli, Gian Luca Foresti

A neural network for image anomaly detection with deep pyramidal representations and dynamic routing (Paper Publication in process.....)

Complete code will be shared as soon as the publcation will be finalised...!!

Reference to datasets-

MvTech Dataset- P. Bergmann, S. L¨owe, M. Fauser, D. Sattlegger and C. Steger, Improving unsupervised defect segmentation by applying structural similarity to autoencoders, International joint conference on computer vision, imaging and computer graphics theory and applications, 2019.

COIL100 Dataset- S. A. Nene, S. K. Nayar and H. Murase, Columbia object image library (coil-100), Tech. Report Technical Report CUCS-006-96, Columbia University(1996)

CIFAR10 Dataset- https://www.cs.toronto.edu/~kriz/cifar.html

MNIST Dataset- Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based learning applied to document recognition." Proceedings of the IEEE, 86(11):2278-2324, November 1998, Link: http://yann.lecun.com/exdb/mnist/