Developing a bio-inspired multi-gene genetic programming based intelligent estimator to reduce speckle noise from ultrasound images

Javed, Syed Gibran; Majid, Abdul; Lee, Yeon Soo

doi:10.1007/s11042-017-5139-2

Cited by 8 publications

(2 citation statements)

References 29 publications

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“…ere was a lack of aesthetics in clothing [15]. Among the clothing patterns, the "articles" to be decorated by the clothing patterns are the clothing itself, and the human body is beautified through the decoration of the clothing, which is the ornamental nature of the patterns.…”

Section: Pattern Feature Analysis Andmentioning

confidence: 99%

Digital Art Pattern Design Based on Visual Material Colouring Intelligent Programming System

Liu

Liang

et al. 2022

Mathematical Problems in Engineering

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With the continuous enhancement of computer technology, digital technology brings more convenience to people with its powerful functions. After the digital technology is applied to the design field, it greatly expands the creative space of art design. In the digital age, fabric printing and dyeing design needs to be combined with digital technology under the guidance of art theory. Traditional flat patterns can no longer satisfy people’s pursuit of visual illusion patterns with a sense of space and three-dimensionality. The use of computer representation can realize the innovative artistic design and can directly generate various highly creative visual images in the computer according to the theme and creative needs. We input the digital data related to the fabric, such as graphics, photographic photos, logos, fonts, and textures, into the computer and then use various application software to perform various special effects on them to produce creative, unique, and surprising picture effects. In the aspect of exploring the meaning of the theme, the application of spatial expression means is studied, and practical research is carried out to guide the design of works with spatial beauty and creativity. In view of the neglect of artistic design, on the basis of studying the space art expression of traditional printing and dyeing process patterns, the traditional space art expression is combined with computer image processing technology. And special techniques are used to create differences in various textile fabrics and garments. We use the software of digital art design to carry out the artistic creation practice of spatial expression. Through the application of computer software functions, combined with the guidance of spatial expression techniques, the design comparison of patterns is carried out, which provides design practice ideas for the integration and innovation of traditional printing and dyeing technology and modern design. The implementation of the visual material colouring programming system reduces the coupling between artists and programmers and reduces the coupling between art collections and producers. The colouring program in the process of art pattern development improves the efficiency of art design.

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Section: Pattern Feature Analysis Andmentioning

confidence: 99%

Digital Art Pattern Design Based on Visual Material Colouring Intelligent Programming System

Liu

Liang

et al. 2022

Mathematical Problems in Engineering

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“…For the whole model, residual learning is a very important technology. Many network models predict a clean image without pollution by learning mapping functions [ 28 ]. For residual learning, it is based on R ( y ) ≈ v function mapping learning image noise residual and then realizes image denoising.…”

Section: Denoising Networkmentioning

confidence: 99%

A Multifeature Extraction Method Using Deep Residual Network for MR Image Denoising

Yao

2020

Computational and Mathematical Methods in Medicine

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In order to improve the resolution of magnetic resonance (MR) image and reduce the interference of noise, a multifeature extraction denoising algorithm based on a deep residual network is proposed. First, the feature extraction layer is constructed by combining three different sizes of convolution kernels, which are used to obtain multiple shallow features for fusion and increase the network’s multiscale perception ability. Then, it combines batch normalization and residual learning technology to accelerate and optimize the deep network, while solving the problem of internal covariate transfer in deep learning. Finally, the joint loss function is defined by combining the perceptual loss and the traditional mean square error loss. When the network is trained, it can not only be compared at the pixel level but also be learned at a higher level of semantic features to generate a clearer target image. Based on the MATLAB simulation platform, the TCGA-GBM and CH-GBM datasets are used to experimentally demonstrate the proposed algorithm. The results show that when the image size is set to 190 × 215 and the optimization algorithm is Adam, the performance of the proposed algorithm is the best, and its denoising effect is significantly better than other comparison algorithms. Especially under high-intensity noise levels, the denoising advantage is more prominent.

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Digital Image Conspicuous Features Classification Using TLCNN Model with SVM Classifier

Rastogi

Duttagupta

Guha

2022

Pattern Recognition and Image Analysis

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Developing a bio-inspired multi-gene genetic programming based intelligent estimator to reduce speckle noise from ultrasound images

Cited by 8 publications

References 29 publications

Digital Art Pattern Design Based on Visual Material Colouring Intelligent Programming System

Digital Art Pattern Design Based on Visual Material Colouring Intelligent Programming System

A Multifeature Extraction Method Using Deep Residual Network for MR Image Denoising

Digital Image Conspicuous Features Classification Using TLCNN Model with SVM Classifier

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