Multi-dimensional complex-valued Gabor wavelet networks

Mak, K. L.; Peng, Pai; Yiu, Ka Fai Cedric; Li, L. K.

doi:10.1016/j.mcm.2013.02.011

Cited by 6 publications

(2 citation statements)

References 40 publications

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“…Several methods have been proposed [43,57] to train the rotation matrix but they are not computationally efficient and hence the rotation parameter of the WNN is often discarded and not used in the training of n-dimensional problem tasks.…”

Section: Learning In Wnnsmentioning

confidence: 99%

Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming

et al. 2017

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Wavelet Neural Networks (WNNs) are complex artificial neural systems and their training can be a challenge. In the past, most common training schemes for WNNs, such as gradient descent, have been restricted to training only a subset of differentiable parameters. In this paper, we propose an evolutionary method to train both differentiable and non-differentiable parameters using the concept of Cartesian Genetic Programming (CGP). The approach was evaluated on the two-spiral task and on real-world datasets for the detection of breast cancer and Parkinson's disease. In our experiments, the performance of the proposed method was comparable to several standard methods of classification. On the breast cancer dataset, the performance was better than other non-ensemble and multistep processing methods. The experimental results show how the performance of WNNs depends on the number of wavelons used. The presented case studies demonstrate that the proposed WNNs perform competitively in comparison to several other methods and results reported in literature.

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Section: Learning In Wnnsmentioning

confidence: 99%

Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming

et al. 2017

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“…On account of extracting much richer texture information, a method based on adaptive weighted sub-Gabor array is presented [10], which contains input variables, complex valued weights, translation parameters and output variables. Generally, the image representations based on Gabor wavelet are widely applied to other pattern recognition fields (e.g., [8,13,14,48]). …”

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confidence: 99%

Face description based on adaptive local weighted Gabor comprehensive histogram feature

Gao

Zhao

Chen

et al. 2016

Multimed Tools Appl

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Face recognition is an extensively research topic in pattern recognition and image processing fields due to its broad application prospects in many areas such as counter terrorism, access identification, electronic passport, e-government affairs, etc. Inspired by the Gabor phase information and local image information content, a novel face description algorithm using adaptive Local Weighted Gabor Comprehensive Histogram (LWGCH) is proposed. It consists of two components: Local Gabor Comprehensive Histogram (LGCH) and Contribution Map (CM). Actually, the adaptive local weighted Gabor comprehensive histogram is generated with LGCH weighed by CM calculated by information content model. Finally, Extensive experiments on ORL, YALE, CMUPIE and Yale B face databases validate the effectiveness of the proposed methods under various conditions of partial occlusion, complex illumination, different expressions and poses. Experimental results indicate that the proposed algorithm is a competitive and robust method compared with several state-of-the-art approaches.

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Fully Complex Valued Wavelet Network for Forecasting the Global Solar Irradiation

Saoud

Rahmoune

Tourtchine

et al. 2016

Neural Process Lett

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Multi-dimensional complex-valued Gabor wavelet networks

Cited by 6 publications

References 40 publications

Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming

Evolving multi-dimensional wavelet neural networks for classification using Cartesian Genetic Programming

Face description based on adaptive local weighted Gabor comprehensive histogram feature

Fully Complex Valued Wavelet Network for Forecasting the Global Solar Irradiation

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