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Evaluation of a Dual Convolutional Neural Network Architecture for
  Object-wise Anomaly Detection in Cluttered X-ray Security Imagery

Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery

10 April 2019
Yona Falinie A. Gaus
Neelanjan Bhowmik
S. Akçay
Paolo M. Guillén-Garcia
Jack W. Barker
T. Breckon
ArXiv (abs)PDFHTML

Papers citing "Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery"

17 / 17 papers shown
Title
Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder
  Anomaly Detection
Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection
S. Akçay
Amir Atapour-Abarghouei
T. Breckon
UQCV
105
381
0
25 Jan 2019
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
S. Akçay
Amir Atapour-Abarghouei
T. Breckon
GAN
97
1,398
0
17 May 2018
An overview of deep learning based methods for unsupervised and
  semi-supervised anomaly detection in videos
An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos
Dilip Ravi Kiran
Mathew Thomas
Ranjith Parakkal
68
448
0
09 Jan 2018
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
1.2K
20,900
0
17 Apr 2017
Mask R-CNN
Mask R-CNN
Kaiming He
Georgia Gkioxari
Piotr Dollár
Ross B. Girshick
ObjD
372
27,253
0
20 Mar 2017
Unsupervised Anomaly Detection with Generative Adversarial Networks to
  Guide Marker Discovery
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
T. Schlegl
Philipp Seeböck
S. Waldstein
U. Schmidt-Erfurth
Georg Langs
MedImGAN
112
2,233
0
17 Mar 2017
Automated detection of smuggled high-risk security threats using Deep
  Learning
Automated detection of smuggled high-risk security threats using Deep Learning
Nicolas Jaccard
T. W. Rogers
E. Morton
Lewis D. Griffin
48
32
0
09 Sep 2016
Automated X-ray Image Analysis for Cargo Security: Critical Review and
  Future Promise
Automated X-ray Image Analysis for Cargo Security: Critical Review and Future Promise
T. W. Rogers
Nicolas Jaccard
E. Morton
Lewis D. Griffin
58
62
0
02 Aug 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB
  model size
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
F. Iandola
Song Han
Matthew W. Moskewicz
Khalid Ashraf
W. Dally
Kurt Keutzer
159
7,501
0
24 Feb 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
382
14,268
0
23 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,510
0
10 Dec 2015
SSD: Single Shot MultiBox Detector
SSD: Single Shot MultiBox Detector
Wen Liu
Dragomir Anguelov
D. Erhan
Christian Szegedy
Scott E. Reed
Cheng-Yang Fu
Alexander C. Berg
ObjDBDL
257
29,879
0
08 Dec 2015
You Only Look Once: Unified, Real-Time Object Detection
You Only Look Once: Unified, Real-Time Object Detection
Joseph Redmon
S. Divvala
Ross B. Girshick
Ali Farhadi
ObjD
735
37,033
0
08 Jun 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal
  Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren
Kaiming He
Ross B. Girshick
Jian Sun
AIMatObjD
533
62,409
0
04 Jun 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,529
0
04 Sep 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLMObjD
1.7K
39,615
0
01 Sep 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
434
43,832
0
01 May 2014
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