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Convolutional neural networks (CNNs) are widely used in many image recognition tasks due to their extraordinary performance.
How should relative changes be measured?
L. Törnqvist, P. Vartia, and Y. O. Vartia · 1985
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The eyes have it: A task by data type taxonomy for information visualizations
B. Shneiderman · 1996
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A visual vocabulary for flower classification
M.-E. Nilsback and A. Zisserman · 2006
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Visual graph comparison
K. Andrews, M. Wohlfahrt, and G. Wurzinger · 2009
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Visualizing higher-layer features of a deep network
D. Erhan, Y. Bengio, A. Courville, and P. Vincent · 2009
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Visual comparison for information visualization
M. Gleicher, D. Albers, R. Walker, I. Jusufi, C. D. Hansen, and J. C. Roberts · 2011
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Weighted graph comparison techniques for brain connectivity analysis
B. Alper, B. Bach, N. Henry Riche, T. Isenberg, and J.-D. Fekete · 2013
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Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
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Deep inside convolutional networks: Visualising image classification models and saliency maps
K. Simonyan, A. Vedaldi, and A. Zisserman · 2013
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Selective search for object recognition
J. R. Uijlings, K. E. Van De Sande, T. Gevers, and A. W. Smeulders · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Convnetjs-deep learning in your browser, 2015
A. Karpathy · 2014
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Large-scale video classification with convolutional neural networks
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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An interactive node-link visualization of convolutional neural networks
Tensorflow: Large-scale machine learning on heterogeneous distributed systems
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A descriptive framework for temporal data visualizations based on generalized space-time cubes
B. Bach, P. Dragicevic, D. Archambault, C. Hurter, and S. Carpendale · 2016
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Inverting visual representations with convolutional networks
A. Dosovitskiy and T. Brox · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg · 2016
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Understanding deep image representations by inverting them
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Direct-manipulation visualization of deep networks
D. Smilkov, S. Carter, D. Sculley, F. B. Viégas, and M. Wattenberg · 2015
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Understanding neural networks through deep visualization
J. Yosinski, J. Clune, A. Nguyen, T. Fuchs, and H. Lipson · 2015
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Y. Luke, H. Greg, M. Joe, and H. Michael · 2016
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A. Nguyen, J. Yosinski, and J. Clune · 2016
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Deeplearning4j: Open-source distributed deep learning for the jvm
Skymind · 2016
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Towards better analysis of deep convolutional neural networks
M. Liu, J. Shi, Z. Li, C. Li, J. Zhu, and S. Liu · 2017
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Visualizing the hidden activity of artificial neural networks
P. E. Rauber, S. G. Fadel, A. X. Falcao, and A. C. Telea · 2017
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