Robust, Deep and Inductive Anomaly Detection

22 April 2017

Papers citing "Robust, Deep and Inductive Anomaly Detection"

13 / 13 papers shown

Title
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models Yunhao Ge Jie Jessie Ren Jiaping Zhao Kaifeng Chen Andrew Gallagher Laurent Itti Balaji Lakshminarayanan VLM ObjD 26 1 0 26 May 2023
Technical outlier detection via convolutional variational autoencoder for the ADMANI breast mammogram dataset Hui Li C. Peña-Solórzano Susan Wei Davis J. McCarthy 22 0 0 20 May 2023
Self-Supervised Training with Autoencoders for Visual Anomaly Detection Alexander Bauer Shinichi Nakajima Klaus-Robert Müller 24 9 0 23 Jun 2022
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection Shaoshen Wang Yanbin Liu Ling Chen Chengqi Zhang 21 0 0 29 May 2022
Utilizing XAI technique to improve autoencoder based model for computer network anomaly detection with shapley additive explanation(SHAP) Khushnaseeb Roshan Aasim Zafar AAML 19 50 0 14 Dec 2021
Normal Learning in Videos with Attention Prototype Network Chao Hu Fan Wu Weijie Wu Weibin Qiu Shengxin Lai 17 1 0 25 Aug 2021
A Survey on Open Set Recognition Atefeh Mahdavi Marco M. Carvalho BDL 21 35 0 18 Aug 2021
Probabilistic Outlier Detection and Generation S. Rizzo L. Pang Yixian Chen S. Chawla 13 0 0 22 Dec 2020
A Critical Evaluation of Open-World Machine Learning Liwei Song Vikash Sehwag A. Bhagoji Prateek Mittal AAML 24 8 0 08 Jul 2020
$$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets$ $(1 + \varepsilon)$ -class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets M. Borisyak Artem Sergeevich Ryzhikov Andrey Ustyuzhanin D. Derkach Fedor Ratnikov Olga Mineeva 7 4 0 14 Jun 2019
Deep CNN-based Multi-task Learning for Open-Set Recognition Poojan Oza Vishal M. Patel 21 35 0 07 Mar 2019
One-Class Convolutional Neural Network Poojan Oza Vishal M. Patel 15 158 0 24 Jan 2019
Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging Xiaoran Chen Nick Pawlowski Martin Rajchl Ben Glocker E. Konukoglu OOD MedIm 22 49 0 14 Jun 2018