1. bookVolume 25 (2015): Issue 4 (December 2015)
    Special issue: Complex Problems in High-Performance Computing Systems, Editors: Mauro Iacono, Joanna Kołodziej
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2083-8492
First Published
05 Apr 2007
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Open Access

Statistical Testing of Segment Homogeneity in Classification of Piecewise–Regular Objects

Published Online: 30 Dec 2015
Volume & Issue: Volume 25 (2015) - Issue 4 (December 2015) - Special issue: Complex Problems in High-Performance Computing Systems, Editors: Mauro Iacono, Joanna Kołodziej
Page range: 915 - 925
Received: 01 Nov 2014
Journal Details
License
Format
Journal
eISSN
2083-8492
First Published
05 Apr 2007
Publication timeframe
4 times per year
Languages
English

Asadpour, V., Homayounpour, M.M. and Towhidkhah, F. (2011). Audio-visual speaker identification using dynamic facial movements and utterance phonetic content, Applied Soft Computing11(2): 2083–2093.10.1016/j.asoc.2010.07.007Search in Google Scholar

Benesty, J., Sondhi, M.M. and Huang, Y. (2008). Springer Handbook of Speech Processing, Springer, Berlin.10.1007/978-3-540-49127-9Search in Google Scholar

Borovkov, A.A. (1998). Mathematical Statistics, Gordon and Breach Science Publishers, Amsterdam.Search in Google Scholar

Bottou, L., Fogelman Soulie, F., Blanchet, P. and Lienard, J. (1990). Speaker-independent isolated digit recognition: Multilayer perceptrons vs. dynamic time warping, Neural Networks3(4): 453–465.Search in Google Scholar

Ciresan, D., Meier, U., Masci, J. and Schmidhuber, J. (2012). Multi-column deep neural network for traffic sign classification, Neural Networks32: 333–338.10.1016/j.neunet.2012.02.02322386783Search in Google Scholar

Dalal, N. and Triggs, B. (2005). Histograms of oriented gradients for human detection, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2005, San Diego, CA, USA, pp. 886–893.Search in Google Scholar

Gray, R., Buzo, A., Gray, A., Jr. and Matsuyama, Y. (1980). Distortion measures for speech processing, IEEE Transactions on Acoustics, Speech and Signal Processing28(4): 367–376.10.1109/TASSP.1980.1163421Search in Google Scholar

Haykin, S.O. (2008). Neural Networks and Learning Machines, 3rd Edn., Prentice Hall, Harlow.Search in Google Scholar

Hinton, G., Deng, L., Yu, D., Dahl, G., Mohamed, A., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T. and Kingsbury, B. (2012). Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups, IEEE Signal Processing Magazine29(6): 82–97.10.1109/MSP.2012.2205597Search in Google Scholar

Hinton, G.E., Osindero, S. and Teh, Y.-W. (2006). A fast learning algorithm for deep belief nets, Neural Computation18(7): 1527–1554.10.1162/neco.2006.18.7.152716764513Search in Google Scholar

Huang, J.-T., Li, J., Yu, D., Deng, L. and Gong, Y. (2013). Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, pp. 7304–7308.Search in Google Scholar

Janakiraman, R., Kumar, J. and Murthy, H. (2010). Robust syllable segmentation and its application to syllable-centric continuous speech recognition, Proceedings of the National Conference on Communications, NCC 2010, Chennai, India, pp. 1–5.Search in Google Scholar

Kullback, S. (1997). Information Theory and Statistics, Dover Publications, New York, NY.Search in Google Scholar

LeCun, Y., Bengio, Y. and Hinton, G. (2015). Deep learning, Nature521(7553): 436–444.10.1038/nature1453926017442Search in Google Scholar

LeCun, Y., Bottou, L., Bengio, Y. and Haffner, P. (1998). Gradient-based learning applied to document recognition, Proceedings of the IEEE86(11): 2278–2324.10.1109/5.726791Search in Google Scholar

Liao, S., Zhu, X., Lei, Z., Zhang, L. and Li, S.Z. (2007). Learning multi-scale block local binary patterns for face recognition, in S.-W. Lee and S.Z. Li (Eds.), Advances in Biometrics, Lecture Notes in Computer Science, Vol. 4642, Springer, Berlin/Heidelberg, pp. 828–837.10.1007/978-3-540-74549-5_87Search in Google Scholar

Lowe, D.G. (2004). Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision60(2): 91–110.10.1023/B:VISI.0000029664.99615.94Search in Google Scholar

Martins, A.F.T., Figueiredo, M.A.T., Aguiar, P.M.Q., Smith, N.A. and Xing, E.P. (2008). Nonextensive entropic kernels, Proceedings of the 25th International Conference on Machine Learning, ICML ’2008, New York, NY, USA, pp. 640–647.Search in Google Scholar

Merialdo, B. (1988). Multilevel decoding for very-large-size-dictionary speech recognition, IBM Journal of Research and Development32(2): 227–237.10.1147/rd.322.0227Search in Google Scholar

Pfau, T. and Ruske, G. (1998). Estimating the speaking rate by vowel detection, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998, Seattle, WA, USA, Vol. 2, pp. 945–948.Search in Google Scholar

Rutkowski, L. (2008). Computational Intelligence: Methods and Techniques, Springer-Verlag, Berlin/Heidelberg.Search in Google Scholar

Sas, J. and Żołnierek, A. (2013). Pipelined language model construction for Polish speech recognition, International Journal of Applied Mathematics and Computer Science23(3): 649–668, DOI: 10.2478/amcs-2013-0049.10.2478/amcs-2013-0049Search in Google Scholar

Savchenko, A.V. (2012). Directed enumeration method in image recognition, Pattern Recognition45(8): 2952–2961.10.1016/j.patcog.2012.02.011Search in Google Scholar

Savchenko, A.V. (2013a). Phonetic words decoding software in the problem of Russian speech recognition, Automation and Remote Control74(7): 1225–1232.10.1134/S000511791307014XSearch in Google Scholar

Savchenko, A.V. (2013b). Probabilistic neural network with homogeneity testing in recognition of discrete patterns set, Neural Networks46: 227–241.10.1016/j.neunet.2013.06.003Search in Google Scholar

Savchenko, A.V. and Khokhlova, Y.I. (2014). About neural-network algorithms application in viseme classification problem with face video in audiovisual speech recognition systems, Optical Memory and Neural Networks (Information Optics)23(1): 34–42.10.3103/S1060992X14010068Search in Google Scholar

Specht, D.F. (1990). Probabilistic neural networks, Neural Networks3(1): 109–118.10.1016/0893-6080(90)90049-QSearch in Google Scholar

Świercz, E. (2010). Classification in the Gabor time-frequency domain of non-stationary signals embedded in heavy noise with unknown statistical distribution, International Journal of Applied Mathematics and Computer Science20(1): 135–147, DOI: 10.2478/v10006-010-0010-x.10.2478/v10006-010-0010-xSearch in Google Scholar

Tan, X., Chen, S., Zhou, Z.-H. and Zhang, F. (2006). Face recognition from a single image per person: A survey, Pattern Recognition39(9): 1725–1745.10.1016/j.patcog.2006.03.013Search in Google Scholar

Theodoridis, S. and Koutroumbas, K. (2008). Pattern Recognition, 4th Edn., Academic Press, Burlington, MA/London.Search in Google Scholar

Zhou, E., Cao, Z. and Yin, Q. (2015). Naive-deep face recognition: Touching the limit of LFW benchmark or not?, CoRRabs/1501.04690.Search in Google Scholar

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