Enhancing Change Point Detection Through Key Actor Identification: A Study in Cryptocurrency Transactions Networks by Ourania Theodosiadou, Andreas Kosmatopoulos, Christos Gkiourtzidis, Taxiarchis Skouras, Theodora Tsikrika, Stefanos Vrochidis, Ioannis Kompatsiaris

“…In addition, feature selection is applied to reduce overlapping information among the extracted features and, finally, change point detection is utilized to identify time locations of significant changes in the selected features. …”
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Detection of Geological Structures in the Gol Gohar Mining Iron Ore Area Using Airborne Magnetic Data by Abdullah Ezam Ahmady, Abdolhamid Ansari, Seyyed Hossein Mojtahedzadeh

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Texture Analysis and Classification using Local Binary Patterns and Statistical Features by Hasan Maher

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Clinical features and genetic analysis of 15 Chinese children with dent disease by Qian Li, Zhenle Yang, Ruixian Zang, Suwen Liu, Lichun Yu, Jing Wang, Cong Wang, Xiaoyuan Wang, Shuzhen Sun

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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…This paper emphasizes the main issues in fraud detection and suggests a novel feature selection method called FID-SOM (feature selection for imbalanced data using SOM). …”
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One-Class Anomaly Detection for Industrial Applications: A Comparative Survey and Experimental Study by Davide Paolini, Pierpaolo Dini, Ettore Soldaini, Sergio Saponara

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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

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ENHANCING NETWORK INTRUSION DETECTION USING MACHINE LEARNING AND META-MODELLING FOR IMPROVED CYBER SECURITY PERFORMANCE by Sunita, Pankaj Verma, Nitika, Jaspreet Kaur, Vijay Rana

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An Agglomerative Clustering Combined with an Unsupervised Feature Selection Approach for Structural Health Monitoring by Tales Boratto, Heder Soares Bernardino, Alex Borges Vieira, Tiago Silveira Gontijo, Matteo Bodini, Dmitriy A. Martyushev, Camila Martins Saporetti, Alexandre Cury, Flávio Barbosa, Leonardo Goliatt

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A Unified Approach to Video Anomaly Detection: Advancements in Feature Extraction, Weak Supervision, and Strategies for Class Imbalance by Rui Z. Barbosa, Hugo S. Oliveira

“…Through comprehensive experimental analysis, the study examines the role of feature representations, sampling strategies, and curriculum learning in enhancing VAD performance. …”
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A Fuzzing Tool Based on Automated Grammar Detection by Jia Song, Jim Alves-Foss

“…We built a fuzzer, called JIMA-Fuzzing, which is an effective fuzzing tool that utilizes grammar detected from sample input. Based on the detected grammar, JIMA-Fuzzing selects a portion of the valid user input and fuzzes that portion. …”
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Detecting forest and linear woody feature change between 1954 and 2019 in Southeastern Canadian agroecosystems for regional biodiversity assessment by Darren Pouliot, Niloofar Alavi, Mao Mao, Jon Pasher, Jason Duffe

“…Effectively mapping and detecting changes in forests and linear woody features (LWFs) is crucial for assessing their impact on biodiversity and ecosystem services. …”
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Advancing Artificial Intelligence of Things Security: Integrating Feature Selection and Deep Learning for Real-Time Intrusion Detection by Faisal Albalwy, Muhannad Almohaimeed

“…The ANN classifier combined with Pearson analysis and PCA achieved the highest intrusion detection accuracy of 99.7%, demonstrating substantial performance improvements over ANN alone (92%) and TabNet (94%) without feature selection. …”
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An Assembled Feature Attentive Algorithm for Automatic Detection of Waste Water Treatment Plants Based on Multiple Neural Networks by Cong Li, Zhengchao Chen, Zhuonan Huang, Yue Shuai, Shaohua Wang, Xiangkun Qi, Jiayi Zheng

“…However, the diverse shapes and scales of WWTPs and their key facilities pose challenges for traditional detection methods. This study employs a Multi-Attention Network (MANet) for WWTP extraction, integrating channel and spatial feature attention. …”
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Accuracy Improvement of Breast Tumor Detection based on Dimension Reduction in the Spatial and Edge Features and Edge Structure in the Image by Samaneh Sadat Seyed Abolghasemi, Mehran Emadi, Mohsen Karimi

“…In this article, a method based on pattern recognition is presented in order to detect the type of tumor. GLCM-based features are extracted from the target area, and Gabor and texture features. …”
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Automated Tomato Leaf Disease Detection Using Image Processing: An SVM-Based Approach with GLCM and SIFT Features by Rashid Khan, Nasir Ud Din, Asim Zaman, Bingding Huang

“…Therefore, we proposed an approach that employs robust feature extraction methods, including the gray level co-occurrence matrix (GLCM) and scale-invariant feature transform (SIFT), coupled with a support vector machine (SVM) for adequate classification. …”
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Multiscale Sample Entropy-Based Feature Extraction with Gaussian Mixture Model for Detection and Classification of Blue Whale Vocalization by Oluwaseyi Paul Babalola, Olayinka Olaolu Ogundile, Vipin Balyan

“…Additionally, MSE is applied to the Gaussian mixture model (GMM) for blue whale call detection and classification. The performance of the proposed MSE-GMM algorithm is experimentally assessed and benchmarked against traditional methods, including principal component analysis (PCA), wavelet-based feature (WF) extraction, and dynamic mode decomposition (DMD), all combined with the GMM. …”
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Improved railway track faults detection using Mel-frequency cepstral coefficient and constant-Q transform features by Rahman Shafique, Khadija Kanwal, Venkata Chunduri, Gyu Sang Choi, Imran Ashraf

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Effective Epileptic Seizure Detection with Hybrid Feature Selection and SMOTE-Based Data Balancing Using SVM Classifier by Hany F. Atlam, Gbenga Ebenezer Aderibigbe, Muhammad Shahroz Nadeem

“…Therefore, this paper presents a novel approach to enhancing epileptic seizure detection through the integration of Synthetic Minority Over-Sampling Technique (SMOTE) for data balancing and a Hybrid Feature Selection Technique—Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT). …”
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Utilizing Enhanced Particle Swarm Optimization for Feature Selection in Gender-Emotion Detection From English Speech Signals by Ammar Amjad, Li-Chia Tai, Hsien-Tsung Chang

“…We extract pitch and acoustic-related statistical features from speech samples and develop separate models for gender prediction and emotion detection. …”
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