Artificial Afterimage Algorithm: A New Bio-Inspired Metaheuristic Algorithm and Its Clustering Application by Murat Demir

“…In this study, a new, metaheuristic method called the afterimage algorithm is proposed. The proposed method was developed inspired by the fact that when we close our eyes after looking at a luminous image for a while, the vision still occurs in our minds. …”
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Novel Automatic Classification Method for Geological Structures in Carbonate Formations Based on Electrical Imaging Logging by FU Yafeng, HUANG Ke, ZHU Hanbin, WANG Hui, ZHANG Xu, ZHAO Jie, XIAO Ni

“…First, an improved K-means clustering algorithm is used to segment regions of interest from the electrical imaging data. …”
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Improved spectral clustering algorithm and its application in MCI detection by Jie XIANG, Dong-qin ZHAO

“…In order to detect mild cognitive impairment (MCI) using functional magnetic resonance imaging (fMRI)，a method based on fMRI clustering was proposed fMRI data were clustered to obtain the blood oxygen level dependence( BOLD) change model of MCI patients，then abnormal patterns were used to detect disease.The traditional spectral clustering algorithm needs to calculate all of the eigenvalue and eigenvector，so time and space complexity is higher.An improved spectral clustering method was proposed which modified the similar matrix construction method and the setting method of σ and k，and then this method was applied to clustering and detection of MCI patients.To verify the performance of the proposed method，the comparison of the clustering result，classification accuracy using traditional algorithm and Nyström is also done.The comparative experimental results show that the proposed method can get BOLD pattern more accurately，the accuracy of MCI detection is higher than the other two algorithms，and the time and space complexity are less than the traditional algorithm.…”
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Improved spectral clustering algorithm and its application in MCI detection by Jie XIANG, Dong-qin ZHAO

“…In order to detect mild cognitive impairment (MCI) using functional magnetic resonance imaging (fMRI)，a method based on fMRI clustering was proposed fMRI data were clustered to obtain the blood oxygen level dependence( BOLD) change model of MCI patients，then abnormal patterns were used to detect disease.The traditional spectral clustering algorithm needs to calculate all of the eigenvalue and eigenvector，so time and space complexity is higher.An improved spectral clustering method was proposed which modified the similar matrix construction method and the setting method of σ and k，and then this method was applied to clustering and detection of MCI patients.To verify the performance of the proposed method，the comparison of the clustering result，classification accuracy using traditional algorithm and Nyström is also done.The comparative experimental results show that the proposed method can get BOLD pattern more accurately，the accuracy of MCI detection is higher than the other two algorithms，and the time and space complexity are less than the traditional algorithm.…”
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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…The methodology consists of computing a difference image using a logarithmic ratio operator, optimizing clustering parameters, computing high-change probability clusters, and generating a refined change map. …”
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Inferring Agronomical Insights for Wheat Canopy Using Image-Based Curve Fit K-Means Segmentation Algorithm and Statistical Analysis by Ankita Gupta, Lakhwinder Kaur, Gurmeet Kaur

“…The proposed algorithm presented here has three stages: (i) first, derivation of dynamic threshold value by curve fitting of data to eliminate the pixels of low-intensity value, (ii) second, extraction and segmentation of thresholded region by application of histogram-based K-means algorithm iteratively (this scheme of the algorithm is referred to as the curve fit K-means (CfitK-means) algorithm); and (iii) third, computation of 23 grey level cooccurrence matrix (GLCM) texture features (traits) from the wheat images has been done. …”
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Crop row centerline extraction method based on regional feature point clustering by Baofeng Ji, Hang Wang, Chunhong Dong, Song Chen, Hongtao Chen, Fazhan Tao, Ji Zhang, Huitao Fan

“…Subsequently, the image is horizontally divided into strips, and the midpoint of each cluster of feature points in each strip is extracted. …”
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Image Matting using Superpixels Centroid by Anam Akbar, Aniqa Shirazi, Mohammad Sarim Farooqui

“…Results are comparable to the different matting algorithms applied independently on images of dataset. …”
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Clustering Analysis of the Energy Mix in Romania Using K-Means Algorithm by Cristina (Antohi) Barbu, Stefan-Mihai Petrea, Corina Sbughea, Cristina Gabriela Zamfir

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Early Warning of Financial Risk Based on K-Means Clustering Algorithm by Zhangyao Zhu, Na Liu

“…The main idea of the K-means clustering algorithm is to gradually optimize clustering results and constantly redistribute target dataset to each clustering center to obtain optimal solution; its biggest advantage lies in its simplicity, speed, and objectivity, being widely used in many research fields such as data processing, image recognition, market analysis, and risk evaluation. …”
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An Improved Density-Based Spatial Clustering of Applications with Noise Algorithm with an Adaptive Parameter Based on the Sparrow Search Algorithm by Zicheng Huang, Zuopeng Liang, Shibo Zhou, Shuntao Zhang

“…This avoids the adverse impact of manually inputting parameters, enabling adaptive clustering with DBSCAN. Experiments on typical synthetic datasets, UCI (University of California, Irvine) real-world datasets, and image segmentation tasks have validated the effectiveness of the SSA-DBSCAN algorithm. …”
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Image Segmentation Based on the Optimized K-Means Algorithm with the Improved Hybrid Grey Wolf Optimization: Application in Ore Particle Size Detection by Xinyi Chai, Zijun Wu, Wei Li, Haowei Fan, Xinyang Sun, Jing Xu

“…In this paper, a novel image segmentation algorithm is proposed, combining the K-means algorithm with a hybridized IGK-means. …”
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An Oil Painters Recognition Method Based on Cluster Multiple Kernel Learning Algorithm by Zhifang Liao, Le Gao, Tian Zhou, Xiaoping Fan, Yan Zhang, Jinsong Wu

“…A lot of image processing research works focus on natural images, such as in classification, clustering, and the research on the recognition of artworks (such as oil paintings), from feature extraction to classifier design, is relatively few. …”
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Image Compression Based on Artificial Intelligent Techniques by Shahbaa Khaleel, Baydaa Khaleel, Alaa khaleel

“…To enhance the performance of the compression system, the first method was developed in two types <em>(k-means 1 dimension run length encoding km1D, k-means 2 dimension run length encoding km2D)</em> by applying traditional clustering algorithm k-means on color and gray level images and then apply compression algorithm RLE in one and two dimension by zigzag scanning to obtain compressed image. …”
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Spatiotemporal correlation–based adaptive sampling algorithm for clustered wireless sensor networks by Wenyu Cai, Meiyan Zhang

“…However, a few sophisticated collection processes of sensory data will consume much more energy than traditional transmission processes such as image and video acquisitions. Given this hypothesis, this article proposed an adaptive sampling algorithm based on temporal and spatial correlation of sensory data for clustered WSNs. …”
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Hybrid Reinforcement Learning-Based Collision Avoidance Algorithm for Autonomous Vehicle Clusters by Chubing Guo, Jianshe Wu, Panzheng Luo, Zhigang Wang, Kai Zhang, Ziyi Yang, Zengfa Dou, Kan Song

“…Nowadays, collaborative collision avoidance for autonomous vehicle clusters has become the key to ensure traffic safety. …”
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LULC-SegNet: Enhancing Land Use and Land Cover Semantic Segmentation with Denoising Diffusion Feature Fusion by Zongwen Shi, Junfu Fan, Yujie Du, Yuke Zhou, Yi Zhang

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Assessing the Effect of Water on Submerged and Floating Plastic Detection Using Remote Sensing and K-Means Clustering by Lenka Fronkova, Ralph P. Brayne, Joseph W. Ribeiro, Martin Cliffen, Francesco Beccari, James H. W. Arnott

“…A K-Means unsupervised clustering algorithm was used to classify the images into two clusters: plastic and water. …”
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Joined Spatial and Spectral Segmentation of Hyperspectral Datasets on Historical Art Objects by Lingxi Liu, Aurore Malmert, Emeline Pouyet, Silvia Mirri, Giovanni Delnevo

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Synthesis of a Generalized Algorithm for Processing and Generating Data on Reflected Signals from Complex Targets by Xung Ha Vo, Trung Kien Nguyen, Phung Bao Nguyen, Quang Hieu Dang

“…To investigate reasons for the formation of complex targets and, using the theory of radar image processing, to synthesize an algorithm for processing and generating data on reflected signals from a complex target.Materials and methods. …”
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