Fetching the paper…
Reading the bibliography…
Identity recognition from ear images is an active field of research within the biometric community.
D. G. Lowe, “Object recognition from local scale-invariant features,” in Computer vision, 1999. The proceedings of the seventh IEEE international conference on , vol. 2. Ieee, 1999, pp. 1150–1157
1999
Earlier work this paper cites.
D. J. Hurley, M. S. Nixon, and J. N. Carter, “Automatic ear recognition by force field transformations,” 2000
2000
Earlier work this paper cites.
H.-J. Zhang, Z.-C. Mu, W. Qu, L.-M. Liu, and C.-Y. Zhang, “A novel approach for ear recognition based on ica and rbf network,” in Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on , vol. 7. IEEE, 2005, pp. 4511–4515
2005
Earlier work this paper cites.
L. Yuan, Z.-c. Mu, Y. Zhang, and K. Liu, “Ear recognition using improved non-negative matrix factorization,” in Pattern Recognition, 2006. ICPR 2006. 18th International Conference on , vol. 4. IEEE, 2006, pp. 501–504
2006
Earlier work this paper cites.
2006
Earlier work this paper cites.
L. Nanni and A. Lumini, “A multi-matcher for ear authentication,” Pattern Recognition Letters , vol. 28, no. 16, pp. 2219–2226, 2007
2007
Earlier work this paper cites.
Y. Guo and Z. Xu, “Ear recognition using a new local matching approach,” in Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on . IEEE, 2008, pp. 289–292
2008
Earlier work this paper cites.
V. Ojansivu, E. Rahtu, and J. Heikkila, “Rotation invariant local phase quantization for blur insensitive texture analysis,” in Pattern Recognition, 2008. ICPR 2008. 19th International Conference on . IEEE, 2008, pp. 1–4
2008
Earlier work this paper cites.
V. Ojansivu and J. Heikkilä, “Blur insensitive texture classification using local phase quantization,” in International conference on image and signal processing . Springer, 2008, pp. 236–243
2008
Earlier work this paper cites.
N.-S. Vu and A. Caplier, “Face recognition with patterns of oriented edge magnitudes,” in European conference on computer vision . Springer, 2010, pp. 313–326
2010
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in neural information processing systems , 2012, pp. 1097–1105
2012
Earlier work this paper cites.
A. Pflug and C. Busch, “Ear biometrics: a survey of detection, feature extraction and recognition methods,” IET biometrics , vol. 1, no. 2, pp. 114–129, 2012
2012
Earlier work this paper cites.
N. Damer and B. Führer, “Ear recognition using multi-scale histogram of oriented gradients,” in Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2012 Eighth International Conference on . IEEE, 2012, pp. 21–24
2012
Earlier work this paper cites.
J. Kannala and E. Rahtu, “Bsif: Binarized statistical image features,” in Pattern Recognition (ICPR), 2012 21st International Conference on . IEEE, 2012, pp. 1363–1366
2012
Earlier work this paper cites.
A. Abaza, A. Ross, C. Hebert, M. A. F. Harrison, and M. S. Nixon, “A survey on ear biometrics,” ACM computing surveys (CSUR) , vol. 45, no. 2, p. 22, 2013
2013
Cited alongside, same era.
2014
Cited alongside, same era.
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell, “Decaf: A deep convolutional activation feature for generic visual recognition.” in Icml , vol. 32, 2014, pp. 647–655
2014
Cited alongside, same era.
D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov, “Scalable object detection using deep neural networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2014, pp. 2147–2154
2014
Cited alongside, same era.
2015
Later among the works it cites.
2015
Later among the works it cites.
2015
Later among the works it cites.
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You only look once: Unified, real-time object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 779–788
2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a deep convolutional network for image super-resolution,” in European Conference on Computer Vision . Springer, 2014, pp. 184–199
2014
Cited alongside, same era.
Z. Cui, H. Chang, S. Shan, B. Zhong, and X. Chen, “Deep network cascade for image super-resolution,” in European Conference on Computer Vision . Springer, 2014, pp. 49–64
2014
Cited alongside, same era.
J. Hu, J. Lu, and Y.-P. Tan, “Discriminative deep metric learning for face verification in the wild,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2014, pp. 1875–1882
2014
Cited alongside, same era.
2014
Cited alongside, same era.
2014
Cited alongside, same era.
L. Jacob and G. Raju, “Ear recognition using texture features-a novel approach,” in Advances in Signal Processing and Intelligent Recognition Systems . Springer, 2014, pp. 1–12
2014
Cited alongside, same era.
2014
Cited alongside, same era.
E. Hoffer and N. Ailon, “Deep metric learning using triplet network,” in International Workshop on Similarity-Based Pattern Recognition . Springer, 2015, pp. 84–92
2015
Cited alongside, same era.
C. Dong, C. C. Loy, K. He, and X. Tang, “Image super-resolution using deep convolutional networks,” IEEE transactions on pattern analysis and machine intelligence , vol. 38, no. 2, pp. 295–307, 2016
2016
Later among the works it cites.
Y. Guo, Y. Liu, A. Oerlemans, S. Lao, S. Wu, and M. S. Lew, “Deep learning for visual understanding: A review,” Neurocomputing , vol. 187, pp. 27–48, 2016
2016
Later among the works it cites.
R. Dellana and K. Roy, “Data augmentation in cnn-based periocular authentication,” in Information Communication and Management (ICICM), International Conference on . IEEE, 2016, pp. 141–145
2016
Later among the works it cites.
2016
Later among the works it cites.
2016
Later among the works it cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 770–778
2016
Later among the works it cites.
P. L. Galdámez, W. Raveane, and A. G. Arrieta, “A brief review of the ear recognition process using deep neural networks,” Journal of Applied Logic , 2016
2016
Later among the works it cites.
K. Grm and V. Struc, “Deep face recognition for smart surveillance applications,” IEEE Intelligent Systems , p. in press, 2017
2017
Closest in time.
Z. Emersic, V. Struc, and P. Peer, “Ear Recognition: More Than a Survey,” Neurocomputing , 2017
2017
Closest in time.