Variable Weighted Ordered Subset Image Reconstruction Algorithm by Jinxiao Pan, Tie Zhou, Yan Han, Ming Jiang

“…We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART) to improve the algebraic reconstruction technique (ART) and simultaneous algebraic reconstruction technique (SART) and establish their convergence. …”
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Improved Bat Algorithm Applied to Multilevel Image Thresholding by Adis Alihodzic, Milan Tuba

“…The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. …”
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An Example-Based Super-Resolution Algorithm for Selfie Images by Jino Hans William, N. Venkateswaran, Srinath Narayanan, Sandeep Ramachandran

“…The proposed algorithm is evaluated for its efficiency and effectiveness both qualitatively and quantitatively with other state-of-the-art SR algorithms. …”
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Mapping Iterative Medical Imaging Algorithm on Cell Accelerator by Meilian Xu, Parimala Thulasiraman

“…Algebraic reconstruction technique (ART) and its variant OS-SART (ordered subset simultaneous ART) are techniques that provide faster convergence with comparatively good image quality. …”
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Research progress of mimic multi-execution scheduling algorithm by Zhengbin ZHU, Qinrang LIU, Dongpei LIU, Chong WANG

“…Mimic defense is the new active defense technology based on the dynamic heterogeneous redundant architecture.With inherent uncertainty, heterogeneous, redundant and negative feedback features, it can significantly improve the robustness and security of system.Among them, the scheduling algorithm is the key to mimic defense technology, which advantages and disadvantages directly affect the ability of system to resist attacks based on known or unknown vulnerabilities.Based on this, the principle and goal of mimic scheduling algorithm were firstly introduced.Then the state-of-the-art of mimic scheduling algorithms were analyzed and summarized from three aspects, such as scheduling object, scheduling quantity and scheduling timing.Finally, the future research direction and trend of mimic scheduling algorithms were prospected.…”
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A Heuristic Algorithm for Resource Allocation/Reallocation Problem by S. Raja Balachandar, K. Kannan

“…The performance of our heuristic is compared with the best state-of-art heuristic algorithms with respect to the quality of the solutions found. …”
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Efficient top-k string similarity query algorithms by Zi-yang CHEN, Yu-jun HAN, Xuan WANG, Jun-feng ZHOU

“…,given a query string σ and string set S,finding k similar strings to σ based on edit distance from S.Firstly,two adaptive filter strategies based on length-skip index are proposed,such that to reduce the times of edit distance computation between two strings.Then the lower bound of edit distance between query string and unmatched string set is proposed,such that to further reduce the times of edit dis-tance computation when processing strings that do not have common signatures with the query string.Finally efficient algorithms to return top-k similar strings are proposed.Experimental results on three real datasets verify the benefits over the state-of-the-art algorithm.…”
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Gamma norm minimization based image denoising algorithm by Hongyan WANG, Tuo WANG, Mian PAN, Zumin WANG

“…Focusing on the issue of rather poor denoising performance of the traditional kernel norm minimization based method caused by the biased approximation of kernel norm to rank function,based on the low-rank theory,a gamma norm minimization based image denoising algorithm was developed.The noisy image was firstly divided into some overlapping patches via the proposed algorithm,and then several non-local image patches most similar to the current image patch were sought adaptively based on the structural similarity index to form the similar image patch matrix.Subsequently,the non-convex gamma norm could be exploited to obtain unbiased approximation of the matrix rank function such that the low-rank denoising model could be constructed.Finally,the obtained low-rank denoising optimization issue could be tackled on the basis of singular value decomposition,and therefore the denoised image patches could be re-constructed as a denoised image.Simulation results demonstrate that,compared to the existing state-of-the-art PID,NLM,BM3D,NNM,WNNM,DnCNN and FFDNet algorithms,the developed method can eliminate Gaussian noise more considerably and retrieve the original image details rather precisely.…”
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Hybridization of DEBOHID with ENN algorithm for highly imbalanced datasets by Sedat Korkmaz

“…Machine learning algorithms assume that datasets are balanced, but most of the datasets in the real world are imbalanced. …”
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Image denoising algorithm based on multi-channel GAN by Hongyan WANG, Xiao YANG, Yanchao JIANG, Zumin WANG

“…Aiming at the issue that the noise generated during image acquisition and transmission would degrade the ability of subsequent image processing, a generative adversarial network (GAN) based multi-channel image denoising algorithm was developed.The noisy color image could be separated into red-green-blue (RGB) three channels via the proposed approach, and then the denoising could be implemented in each channel on the basis of an end-to-end trainable GAN with the same architecture.The generator module of GAN was constructed based on the U-net derivative network and residual blocks such that the high-level feature information could be extracted effectively via referring to the low-level feature information to avoid the loss of the detail information.In the meantime, the discriminator module could be demonstrated on the basis of fully convolutional neural network such that the pixel-level classification could be achieved to improve the discrimination accuracy.Besides, in order to improve the denoising ability and retain the image detail as much as possible, the composite loss function could be depicted by the illustrated denoising network based on the following three loss measures, adversarial loss, visual perception loss, and mean square error (MSE).Finally, the resultant three-channel output information could be fused by exploiting the arithmetic mean method to obtain the final denoised image.Compared with the state-of-the-art algorithms, experimental results show that the proposed algorithm can remove the image noise effectively and restore the original image details considerably.…”
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Novel image registration algorithm for scene-matching navigation by Hongrui YANG, Qiju ZHU, Peixian CAO, Hao GU, Dongdong ZHAO

“…Our framework has been rigorously evaluated across diverse multimodal image pairs, including optical–optical, optical–SAR, and optical–hyperspectral datasets. Our algorithm has been compared with current state-of-the-art image registration methods, including traditional feature–based approaches such as DSOG, histogram of oriented phase congruency (HOPC), and radiation-variation insensitive feature transform (RIFT), as well as deep learning–based techniques such as Loftr and Superpoint. …”
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Retracted: Research on the Application of Genetic Algorithm in Physical Education by Journal of Mathematics

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Retracted: Iris Localization Algorithm based on Effective Area by International Journal of Antennas and Propagation

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Retracted: Study on the Macroeconomic Model Based on the Genetic Algorithm by Applied Bionics and Biomechanics

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Research on the Algorithms for Registration in Sensor Network for Target Tracking by Ling Wu, Fa-Xing Lu

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Computing Cupid: Online Dating and the Faith of Romantic Algorithms by Sokfa F. John

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General Influence Coefficient Algorithm in Balancing of Rotating Machinery by Yu Xiaoping

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Parallel deduction-search algorithm for the predicate logic formulas by Stasys Norgėla

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Treatment Algorithm for Acute Kidney Injury in Patients with Cirrhosis by Myeong Jun Song

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On the Shock-Response-Spectrum Recursive Algorithm of Kelly and Richman by Justin N. Martin, Andrew J. Sinclair, Winfred A. Foster

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