Entropy feature and peak-means clustering based slowly moving object detection in head and shoulder video sequences by Prabodh Kumar Sahoo, Priyadarshi Kanungo, Satyasis Mishra, Bibhu Prasad Mohanty

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Clustering-Based Pattern Abnormality Detection in Distributed Sensor Networks by Seok-Woo Jang, Gye-Young Kim, Siwoo Byun

“…The experiments conducted in this work prove that our suggested clustering-based algorithm effectively detects various traffic attacks.…”
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Automatic Detection and Unsupervised Clustering-Based Classification of Cetacean Vocal Signals by Yinian Liang, Yan Wang, Fangjiong Chen, Hua Yu, Fei Ji, Yankun Chen

“…To extract useful features from a large amount of PAM data for classifying different cetacean species, we propose an automatic detection and unsupervised clustering-based classification method for cetacean vocal signals. …”
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Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection by J. Pérez-Aracil, C. Peláez-Rodríguez, Ronan McAdam, Antonello Squintu, Cosmin M. Marina, Eugenio Lorente-Ramos, Niklas Luther, Verónica Torralba, Enrico Scoccimarro, Leone Cavicchia, Matteo Giuliani, Eduardo Zorita, Felicitas Hansen, David Barriopedro, Ricardo García-Herrera, Pedro A. Gutiérrez, Jürg Luterbacher, Elena Xoplaki, Andrea Castelletti, S. Salcedo-Sanz

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EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking by Tran Hiep Dinh, Avinash Kumar Singh, Nguyen Linh Trung, Diep N. Nguyen, Chin-Teng Lin

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An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method by Deepa Devasenapathy, Kathiravan Kannan

“…Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. …”
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Intrusion detection in cluster‐based wireless sensor networks: Current issues, opportunities and future research directions by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Muhammed Faheem

“…In addition, this research conducted several comparative studies of feature selection techniques and machine learning methodologies in the development of intrusion detection systems. …”
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Hybrid Model for Novel Attack Detection Using a Cluster-Based Machine Learning Classification Approach for the Internet of Things (IoT) by Naveed Ahmed, Md Asri Ngadi, Abdulaleem Ali Almazroi, Nouf Atiahallah Alghanmi

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Analysis and Selection Method for Radar Echo Features in Challenging Scenarios by Yunlong Dong, Xiao Luo, Hao Ding, Ningbo Liu, Zheng Cao

“…In addressing the issue of weak target detection at sea, most existing feature detection methods are designed for scenarios with low sea states and small grazing angles. …”
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Effective defense against physically embedded backdoor attacks via clustering-based filtering by Mohammed Kutbi

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Research on performance optimizations for TCM-KNN network anomaly detection algorithm by LI Yang1, GUO Li1, LU Tian-bo3, TIAN Zhi-hong1

“…Based on TCM-KNN（transductive confidence machine for K-nearest neighbors） algorithm,the filter-based feature selection and cluster-based instance selection methods were used towards optimizing it as a lightweight network anomaly detection scheme,which not only reduced its complex feature space,but also acquired high quality instances for training.A series of experimental results demonstrate the two methods for optimizations are actually effective in greatly reducing the computational costs while ensuring high detection performances for TCM-KNN algorithm.Therefore,the two methods make TCM-KNN be a good scheme for a lightweight network anomaly detection in practice.…”
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Detection of Potentially Anomalous Cosmic Particle Tracks Acquired with CMOS Sensors: Validation of Rough k–Means Clustering with PCA Feature Extraction by Hachaj Tomasz, Piekarczyk Marcin, Wąs Jarosław

“…We apply a principal components analysis-based feature extraction method and rough k-means clustering for outlier detection. …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…In this paper, we propose a novel framework for detecting anomalies in videos by uniquely analyzing spatial and temporal (spatio-temporal) features. …”
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Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation by Gunjan Shandilya, Sheifali Gupta, Ahmad Almogren, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

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Generating Deeply-Engineered Technical Features for Basketball Video Understanding by Shaohua Fang, Guifeng Wang, Yongbin Li, Yue Yu, Jun Li

“…Our main contributions include: 1) an LSTM-based deep learning architecture for player action recognition and prediction; 2) a clustering-based algorithm for basketball court and line detection; and 3) a keyframe selection technique for basketball videos based on spatial-temporal scoring. …”
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Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…These challenges arise from the need to simultaneously detect community structures and track their evolutionary behaviors. …”
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Image Processing Using Feature-Based Segmentation Techniques for the Analysis of Medical Images by Christodoss Prasanna Ranjith, Krishnamoorthy Natarajan, Sindhu Madhuri, Mahesh Thylore Ramakrishna, Chandrasekhar Rohith Bhat, Vinoth Kumar Venkatesan

“…Unlike classic K-means, which requires you to choose the number of clusters before executing the algorithm, adaptive K-means identifies the best number of clusters based on the features of the data. The proposed model works as follows. …”
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Singular-Value-Based Cluster Number Detection Method by Yating Li, Jianghui Cai, Haifeng Yang, Jie Wang, Chenhui Shi, Bo Liang, Xujun Zhao, Yaling Xun

“…The number of larger singular values may correspond to the number of clusters, and their main information may correspond to different clusters. Based on this, a singular-value-based cluster number detection method is proposed. …”
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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…The task of outlier detection involves identifying these points and analyzing their potential abnormal information through the analysis of data attribute features. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…As the bolt with missing pins are small targets, their positioning is difficult and their features are hard to extract. Aim at this problem, a detection method for bolts with missing pins is proposed based on the DBSCAN algorithm and FPN model. …”
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