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Visual Concept Networks: A Graph-Based Approach to Detecting Anomalous
  Data in Deep Neural Networks

Visual Concept Networks: A Graph-Based Approach to Detecting Anomalous Data in Deep Neural Networks

26 September 2024
Debargha Ganguly
Debayan Gupta
Vipin Chaudhary
    GNN
ArXiv (abs)PDFHTML

Papers citing "Visual Concept Networks: A Graph-Based Approach to Detecting Anomalous Data in Deep Neural Networks"

14 / 14 papers shown
Title
Out-of-Distribution Detection with Deep Nearest Neighbors
Out-of-Distribution Detection with Deep Nearest Neighbors
Yiyou Sun
Yifei Ming
Xiaojin Zhu
Yixuan Li
OODD
200
520
0
13 Apr 2022
Detecting Twenty-thousand Classes using Image-level Supervision
Detecting Twenty-thousand Classes using Image-level Supervision
Xingyi Zhou
Rohit Girdhar
Armand Joulin
Phillip Krahenbuhl
Ishan Misra
CLIPVLM
103
614
0
07 Jan 2022
A Survey on Open Set Recognition
A Survey on Open Set Recognition
Atefeh Mahdavi
Marco M. Carvalho
BDL
69
35
0
18 Aug 2021
CSKG: The CommonSense Knowledge Graph
CSKG: The CommonSense Knowledge Graph
Filip Ilievski
Pedro A. Szekely
Bin Zhang
78
89
0
21 Dec 2020
Energy-based Out-of-distribution Detection
Energy-based Out-of-distribution Detection
Weitang Liu
Xiaoyun Wang
John Douglas Owens
Yixuan Li
OODD
271
1,356
0
08 Oct 2020
A Unifying Review of Deep and Shallow Anomaly Detection
A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff
Jacob R. Kauffmann
Robert A. Vandermeulen
G. Montavon
Wojciech Samek
Marius Kloft
Thomas G. Dietterich
Klaus-Robert Muller
UQCV
117
800
0
24 Sep 2020
Scaling Out-of-Distribution Detection for Real-World Settings
Scaling Out-of-Distribution Detection for Real-World Settings
Dan Hendrycks
Steven Basart
Mantas Mazeika
Andy Zou
Joe Kwon
Mohammadreza Mostajabi
Jacob Steinhardt
Basel Alomair
OODD
180
481
0
25 Nov 2019
LVIS: A Dataset for Large Vocabulary Instance Segmentation
LVIS: A Dataset for Large Vocabulary Instance Segmentation
Agrim Gupta
Piotr Dollár
Ross B. Girshick
ISegVLM
103
1,371
0
08 Aug 2019
Deep Anomaly Detection with Outlier Exposure
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks
Mantas Mazeika
Thomas G. Dietterich
OODD
183
1,483
0
11 Dec 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and
  Adversarial Attacks
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee
Kibok Lee
Honglak Lee
Jinwoo Shin
OODD
187
2,051
0
10 Jul 2018
graph2vec: Learning Distributed Representations of Graphs
graph2vec: Learning Distributed Representations of Graphs
A. Narayanan
Mahinthan Chandramohan
R. Venkatesan
Lihui Chen
Yang Liu
Shantanu Jaiswal
GNN
71
742
0
17 Jul 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples
  in Neural Networks
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks
Kevin Gimpel
UQCV
164
3,454
0
07 Oct 2016
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
277
19,066
0
20 Dec 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
413
43,667
0
01 May 2014
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