Fetching the paper…
Reading the bibliography…
Due to the rapid growth of machine learning tools and specifically deep networks in various computer vision and image processing areas, application of Convolutional Neural Networks for watermarking have recently emerged.
X. Liu, G. Han, J. Wu, Z. Shao, G. Coatrieux, H. Shu, Fractional Krawtchouk transform with an application to image watermarking, IEEE Transactions on Signal Processing 65 (7) (2017) 1894–1908
1908
Earlier work this paper cites.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, R. Salakhutdinov, Dropout: a simple way to prevent neural networks from overfitting, The Journal of Machine Learning Research 15 (1) (2014) 1929–1958
1958
Earlier work this paper cites.
W. Szepanski, A signal theoretic method for creating forgery-proof documents for automatic verification 101 (109) (1979) 368
1979
Earlier work this paper cites.
R. S. Broughton, W. C. Laumeister, Interactive video method and apparatus (1989)
1989
Earlier work this paper cites.
I. Daubechies, W. Sweldens, Factoring wavelet transforms into lifting steps, Journal of Fourier analysis and applications 4 (3) (1998) 247–269
1998
Earlier work this paper cites.
Y. Cheng, Music database retrieval based on spectral similarity, 2nd Int. Sympo-sium on Music Information Retrieval (IS-MIR), Oct., 2001
2001
Earlier work this paper cites.
R.-Z. Wang, C.-F. Lin, J.-C. Lin, Image hiding by optimal LSB substitution and genetic algorithm, Pattern recognition 34 (3) (2001) 671–683
2001
Earlier work this paper cites.
B. Chen, G. W. Wornell, Quantization index modulation: A class of provably good methods for digital watermarking and information embedding, IEEE Transactions on Information Theory 47 (4) (2001) 1423–1443
2001
Earlier work this paper cites.
Z. Zhi-Ming, L. Rong-Yan, W. Lei, Adaptive watermark scheme with RBF neural networks, in: Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on, Vol. 2, IEEE, 2003, pp. 1517–1520
2003
Earlier work this paper cites.
M. Hagmüller, H. Hering, A. Kröpfl, G. Kubin, Speech watermarking for air traffic control, Watermark 8 (9) (2004) 10
2004
Earlier work this paper cites.
I. Cox, M. Miller, J. Bloom, J. Fridrich, T. Kalker, Digital watermarking and steganography, Morgan kaufmann, 2007
2007
Earlier work this paper cites.
M. Faundez-Zanuy, M. Hagmüller, G. Kubin, Speaker identification security improvement by means of speech watermarking, Pattern recognition 40 (11) (2007) 3027–3034
2007
Earlier work this paper cites.
L. Sanping, Z. Yusen, Z. Hui, A wavelet-domain watermarking technique based on support vector regression, in: Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on, IEEE, 2007, pp. 1112–1116
2007
Earlier work this paper cites.
W. W. Y. Ng, A. Dorado, D. S. Yeung, W. Pedrycz, E. Izquierdo, Image classification with the use of radial basis function neural networks and the minimization of the localized generalization error, Pattern Recognition 40 (1) (2007) 19–32
2007
Earlier work this paper cites.
2007
Earlier work this paper cites.
A. Khan, S. F. Tahir, A. Majid, T.-S. Choi, Machine learning based adaptive watermark decoding in view of anticipated attack, Pattern Recognition 41 (8) (2008) 2594–2610
2008
Cited alongside, same era.
doi:10.1109/TNN.2010.2040192
M. Narwaria, W. Lin, Objective image quality assessment based on support vector regression. , IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council 21 (3) (2010) 515–9 · 2010
Cited alongside, same era.
L. Ma, M. M. Crawford, J. Tian, Local manifold learning-based k k -nearest-neighbor for hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing 48 (11) (2010) 4099–4109
2010
Cited alongside, same era.
M. Everingham, L. Van˜Gool, C. K. I. Williams, J. Winn, A. Zisserman, The PASCAL visual object classes challenge 2012 (VOC2012) results, http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html
2012
Cited alongside, same era.
F. N. Thakkar, V. K. Srivastava, A blind medical image watermarking: DWT-SVD based robust and secure approach for telemedicine applications, Multimedia Tools and Applications 76 (3) (2017) 3669–3697
2017
Later among the works it cites.
doi:10.1134/S1054661817030257
D. G. Savakar, A. Ghuli, Non-blind digital watermarking with enhanced image embedding capacity using DMeyer wavelet decomposition, SVD, and DFT , Pattern Recognition and Image Analysis 27 (3) (2017) 511–517 · 2017
Later among the works it cites.
M. Heidari, S. Samavi, S. M. R. Soroushmehr, S. Shirani, N. Karimi, K. Najarian, Framework for robust blind image watermarking based on classification of attacks, Multimedia Tools and Applications 76 (22) (2017) 23459–23479
2017
Later among the works it cites.
Z. Zheng, L. Zheng, Y. Yang, A discriminatively learned CNN embedding for person reidentification, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 14 (1) (2017) 13
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
E. Pasolli, F. Melgani, D. Tuia, F. Pacifici, W. J. Emery, SVM active learning approach for image classification using spatial information, IEEE Transactions on Geoscience and Remote Sensing 52 (4) (2014) 2217–2233
2014
Cited alongside, same era.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio, Generative adversarial nets, in: Advances in neural information processing systems, 2014, pp. 2672–2680
2014
Cited alongside, same era.
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, C. L. Zitnick, Microsoft coco: Common objects in context, in: European conference on computer vision, Springer, 2014, pp. 740–755
2014
Cited alongside, same era.
S. Ren, K. He, R. Girshick, J. Sun, Faster R-CNN: Towards real-time object detection with region proposal networks, in: Advances in neural information processing systems, 2015, pp. 91–99
2015
Cited alongside, same era.
A. K. Singh, M. Dave, A. Mohan, Robust and secure multiple watermarking in wavelet domain, Journal of medical imaging and health informatics 5 (2) (2015) 406–414
2015
Cited alongside, same era.
O. Benrhouma, H. Hermassi, A. A. A. El-Latif, S. Belghith, Chaotic watermark for blind forgery detection in images, Multimedia Tools and Applications 75 (14) (2016) 8695–8718
2016
Cited alongside, same era.
R. P. Singh, N. Dabas, V. Chaudhary, Online sequential extreme learning machine for watermarking in DWT domain, Neurocomputing 174 (2016) 238–249
2016
Cited alongside, same era.
K. He, X. Zhang, S. Ren, 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
Cited alongside, same era.
G. Huang, Z. Liu, L. Van Der Maaten, K. Q. Weinberger, Densely Connected Convolutional Networks. 1 (2) (2017) 3
2017
Later among the works it cites.
H. Kandi, D. Mishra, S. R. S. Gorthi, Exploring the learning capabilities of convolutional neural networks for robust image watermarking, Computers & Security 65 (2017) 247–268
2017
Later among the works it cites.
H. Fazlali, S. Samavi, N. Karimi, S. Shirani, Adaptive blind image watermarking using edge pixel concentration, Multimedia Tools and Applications 76 (2) (2017) 3105–3120
2017
Later among the works it cites.
N. M. Makbol, B. E. Khoo, T. H. Rassem, K. Loukhaoukha, A new reliable optimized image watermarking scheme based on the integer wavelet transform and singular value decomposition for copyright protection, Information Sciences 417 (2017) 381–400
2017
Later among the works it cites.
A. Shehab, M. Elhoseny, K. Muhammad, A. K. Sangaiah, P. Yang, H. Huang, G. Hou, Secure and robust fragile watermarking scheme for medical images, IEEE Access 6 (2018) 10269–10278
2018
Closest in time.
doi:10.1007/s11042-018-5759-1
G. Anbarjafari, C. Ozcinar, Imperceptible non-blind watermarking and robustness against tone mapping operation attacks for high dynamic range images, Multimedia Tools and Applications 77 (18) (2018) 24521–24535 · 2018
Closest in time.
A. M. Abdelhakim, M. Abdelhakim, A time-efficient optimization for robust image watermarking using machine learning, Expert Systems with Applications 100 (2018) 197–210
2018
Closest in time.
S. Etemad, M. Amirmazlaghani, A new multiplicative watermark detector in the contourlet domain using t location-scale distribution, Pattern Recognition 77 (2018) 99–112
2018
Closest in time.
J. Li, C. Yu, B. B. Gupta, X. Ren, Color image watermarking scheme based on quaternion Hadamard transform and Schur decomposition, Multimedia Tools and Applications 77 (4) (2018) 4545–4561
2018
Closest in time.
E. Etemad, S. Samavi, S. R. Soroushmehr, N. Karimi, M. Etemad, S. Shirani, K. Najarian, Robust image watermarking scheme using bit-plane of hadamard coefficients, Multimedia Tools and Applications 77 (2) (2018) 2033–2055
2055
Closest in time.