Data augmentation and pre-trained networks for extremely low data regimes unsupervised visual inspection

2 June 2021

Papers citing "Data augmentation and pre-trained networks for extremely low data regimes unsupervised visual inspection"

28 / 28 papers shown

Title
Synthetic training data generation for deep learning based quality inspection Pierre Gutierrez Maria Luschkova Antoine Cordier Mustafa Shukor Mona Schappert Tim Dahmen 37 21 0 07 Apr 2021
Active learning using weakly supervised signals for quality inspection Antoine Cordier Deepan Das Pierre Gutierrez 41 7 0 07 Apr 2021
DFR: Deep Feature Reconstruction for Unsupervised Anomaly Segmentation Jie Yang Yong Shi Zhiquan Qi UQCV 138 120 0 13 Dec 2020
Multiresolution Knowledge Distillation for Anomaly Detection Mohammadreza Salehi Niousha Sadjadi Soroosh Baselizadeh M. Rohban Hamid R. Rabiee 132 443 0 22 Nov 2020
PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization Thomas Defard Aleksandr Setkov Angélique Loesch Romaric Audigier UQCV 79 848 0 17 Nov 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances Jihoon Tack Sangwoo Mo Jongheon Jeong Jinwoo Shin OODD 85 604 0 16 Jul 2020
Explainable Deep One-Class Classification Philipp Liznerski Lukas Ruff Robert A. Vandermeulen Billy Joe Franks Marius Kloft Klaus-Robert Muller 66 199 0 03 Jul 2020
Task-agnostic Out-of-Distribution Detection Using Kernel Density Estimation Ertunc Erdil K. Chaitanya Neerav Karani E. Konukoglu OODD 43 7 0 18 Jun 2020
Rethinking Assumptions in Deep Anomaly Detection Lukas Ruff Robert A. Vandermeulen Billy Joe Franks Klaus-Robert Muller Marius Kloft 83 90 0 30 May 2020
Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection Oliver Rippel Patrick Mertens Dorit Merhof 133 240 0 28 May 2020
Classification-Based Anomaly Detection for General Data Liron Bergman Yedid Hoshen 54 351 0 05 May 2020
Sub-Image Anomaly Detection with Deep Pyramid Correspondences Niv Cohen Yedid Hoshen 84 477 0 05 May 2020
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study Christoph Baur Stefan Denner Benedikt Wiestler Shadi Albarqouni Nassir Navab OOD 77 292 0 07 Apr 2020
Why is the Mahalanobis Distance Effective for Anomaly Detection? Ryo Kamoi Kei Kobayashi OODD 177 58 0 01 Mar 2020
Deep Nearest Neighbor Anomaly Detection Liron Bergman Niv Cohen Yedid Hoshen UQCV 87 160 0 24 Feb 2020
Novelty Detection Via Blurring Sung-Ik Choi Sae-Young Chung UQCV 49 36 0 27 Nov 2019
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings Paul Bergmann Michael Fauser David Sattlegger C. Steger 84 666 0 06 Nov 2019
End-to-End Defect Detection in Automated Fiber Placement Based on Artificially Generated Data S. Zambal Christoph Heindl C. Eitzinger J. Scharinger 26 27 0 11 Oct 2019
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty Dan Hendrycks Mantas Mazeika Saurav Kadavath Basel Alomair OOD SSL 56 950 0 28 Jun 2019
Deep Semi-Supervised Anomaly Detection Lukas Ruff Robert A. Vandermeulen Nico Görnitz Alexander Binder Emmanuel Müller K. Müller Marius Kloft UQCV 58 547 0 06 Jun 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 164 18,193 0 28 May 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 183 1,487 0 11 Dec 2018
Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders Paul Bergmann Sindy Löwe Michael Fauser David Sattlegger C. Steger 81 669 0 05 Jul 2018
Deep Anomaly Detection Using Geometric Transformations I. Golan Ran El-Yaniv 97 607 0 28 May 2018
Learning Deep Features for One-Class Classification Pramuditha Perera Vishal M. Patel 116 371 0 16 Jan 2018
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery T. Schlegl Philipp Seeböck S. Waldstein U. Schmidt-Erfurth Georg Langs MedIm GAN 112 2,233 0 17 Mar 2017
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.9K 77,441 0 18 May 2015
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks Ian Goodfellow M. Berk Mirza Xia Da Aaron Courville Yoshua Bengio 156 1,455 0 21 Dec 2013