Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering by Liulong Yao, Jinrong Cui, Yazi Xie, Chengli Sun

“…Extensive experiments on five benchmark datasets show that our proposed method outperforms most other clustering algorithms.…”
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Identifying chronic pain subgroups in the UK biobank for persona development: A clustering analysis by Ting-Chen Chloe Hsu, Pauline Whelan, Christopher J Armitage, John McBeth

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Pixel-wise navigation line extraction of cross-growth-stage seedlings in complex sugarcane fields and extension to corn and rice by Hongwei Li, Hongwei Li, Xindong Lai, Yongmei Mo, Deqiang He, Tao Wu, Tao Wu

“…In response to such challenges, we proposed a generalizable navigation line extraction algorithm using classical image processing technologies. …”
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Fast Detection of Idler Supports Using Density Histograms in Belt Conveyor Inspection with a Mobile Robot by Janusz Jakubiak, Jakub Delicat

“…The detection algorithm utilizes density histograms, Euclidean clustering, and a dimension-based classifier. …”
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Radiometric landscape: a new conceptual framework and operational approach for landscape characterisation and mapping by Louise Lemettais, Samuel Alleaume, Sandra Luque, Anne-Élisabeth Laques, Yonas Alim, Laurent Demagistri, Agnès Bégué

“…The parameterization of the segmentation and clustering algorithms is determined by statistical optimization. …”
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A good neighbor is a great blessing: Nearest neighbor filtering method to remove impulse noise by Mohd Rafi Lone, Ekram Khan

“…Impulse noise is one of the common noise types that affect images. Median filtering denoising method has been widely used for impulse noise. …”
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Vibe++ background segmentation method combining MeanShift clustering analysis and convolutional neural network by Zihao LIU, Xiaojun JIA, Sulan ZHANG, Zhiling XU, Jun ZHANG

“…To solve problems of noise points and high segmentation error for image shadow brought by traditional Vibe+ algorithm, a novel background segmentation method (Vibe++) based on the improved Vibe+ was proposed.Firstly, binarization image was acquired by using traditional Vibe+ algorithm from surveillance video.The connected regions were marked based on the region-growing domain marker method.The area threshold was obtained with difference characteristics of boundary area, the connected regions below threshold were treated as disturbing points.Secondly, five different kernel functions were introduced to improve the traditional MeanShift clustering algorithm.After improving, this algorithm was fused effectively with partitioned convolutional neural network.Finally, program of classification of trailing area, non-trailing area and trailing edge area in the resulting image was performed.Position coordinates of the trailing area were calculated and confirmed, and the trailing area was quickly deleted to obtain the final segmentation result.This segmentation accuracy was greatly improved by using the proposed method.The experimental results show that the proposed algorithm can achieve segmentation accuracy of more than 98% and has good application effect and high practical value.…”
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Optimizing Solar Energy Harvesting: A K‐Means Clustering Approach for Enhanced Efficiency and Viability by Li Bin, Muhammad Shahzad, Muhammad Farhan, Muhammad Sanaullah Khan, Mubaarak Abdulrahman Abdu Saif, Girmaw Teshager Bitew

“…This research introduces an innovative synthesis method for a typical solar radiation year (TSRY) based on K‐means clustering to maximize energy harvest. The K‐means algorithm, a fundamental image processing technique, is utilized to classify images into distinct groups. …”
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Student Performance Prediction Using Machine Learning Algorithms by Esmael Ahmed

“…Some areas of applications of ML algorithms include cluster analysis, pattern recognition, image processing, natural language processing, and medical diagnostics. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…As part of this study, we compared the outputs generated by two unsupervised machine learning algorithms with a conventional image clustering technique. …”
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Study on the fusion of improved YOLOv8 and depth camera for bunch tomato stem picking point recognition and localization by Guozhu Song, Jian Wang, Rongting Ma, Yan Shi, Yaqi Wang

“…Subsequently, the optimized K-means algorithm, utilizing K-means++ for clustering centre initialization and determining the optimal number of clusters via Silhouette coefficients, is employed to segment the fruit stalk region. …”
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GDnet-IP: Grouped Dropout-Based Convolutional Neural Network for Insect Pest Recognition by Dongcheng Li, Yongqi Xu, Zheming Yuan, Zhijun Dai

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GPR Diffraction Separation by Incorporating Multilevel Wavelet Transform and Multiple Singular Spectrum Analysis by Haolin Wang, Honghua Wang, Zhiyang Hou, Fei Zhou

“…Building upon this, the <i>k</i>-means clustering algorithm is introduced to perform MSSA for classifying singular values into <i>k</i> categories. …”
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Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning. by Jiayi Wu, Yong-Bei Ma, Charles Congdon, Bevin Brett, Shuobing Chen, Yaofang Xu, Qi Ouyang, Youdong Mao

“…However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. …”
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SIFT Feature-Based Video Camera Boundary Detection Algorithm by Lingqiang Kong

“…Aiming at the problem of low accuracy of edge detection of the film and television lens, a new SIFT feature-based camera detection algorithm was proposed. Firstly, multiple frames of images are read in time sequence and converted into grayscale images. …”
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Real-Time Human Group Detection and Clustering in Crowded Environments Using Enhanced Multi-Object Tracking by Hyunmin Lee, Donggoo Kang, Hasil Park, Sangwoo Park, Dasol Jeong, Joonki Paik

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Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling by Xueqian Gong, Zhanyuan Zhu, Li Guo, Yong Zhong, Deshun Zhang, Jing Li, Manqin Yao, Wei Yong, Mengjia Li, Yujie Huang

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A multi-task genetic programming approach for online multi-objective container placement in heterogeneous cluster by Ruochen Liu, Haoyuan Lv, Ping Yang, Rongfang Wang

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Improved SOM algorithm for damage characterization based on visual sensing by Hongtao Zhu, Shuyun Guo

“…Additionally, employing stochastic gradient descent as an optimization algorithm enhances the model training efficiency. Experimental results showcase that the model exhibits a detection time of merely 0.8 seconds, while demonstrating outstanding fitting and clustering performance, achieving an actual accuracy of 98.2%. …”
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YOLOX-S-TKECB: A Holstein Cow Identification Detection Algorithm by Hongtao Zhang, Li Zheng, Lian Tan, Jiahui Gao, Yiming Luo

“…Therefore, this paper proposes a cow identification method based on YOLOX-S-TKECB. (1) Based on the characteristics of Holstein cows and their breeding practices, we constructed a real-time acquisition and preprocessing platform for two-dimensional Holstein cow images and built a cow identification model based on YOLOX-S-TKECB. (2) Transfer learning was introduced to improve the convergence speed and generalization ability of the cow identification model. (3) The CBAM attention mechanism module was added to enhance the model’s ability to extract features from cow torso patterns. (4) The alignment between the apriori frame and the target size was improved by optimizing the clustering algorithm and the multi-scale feature fusion method, thereby enhancing the performance of object detection at different scales. …”
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