Theoretical approaches to detecting anomalies in meter readings in scientific literature by D.V. Furikhata, T.A. Vakalyuk

“…The paper provides a comprehensive analysis of existing methods for detecting anomalies, which are classified into three main categories: point anomalies, which represent individual deviations from the typical consumption pattern; contextual anomalies, which depend on the specific temporal or spatial environment; and collective anomalies, which arise in groups of interrelated data. …”
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Ultrasound elastography: advances and challenges in early detection of breast cancer by Jianmin Zhou, Yanchun Zhang, Shaohua Shi

“…Artificial intelligence integration has transformed breast elastography workflow, introducing sophisticated pattern recognition and automated lesion characterization. …”
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Automatic Card Fraud Detection Based on Decision Tree Algorithm by Elena Flondor, Liliana Donath, Mihaela Neamtu

“…Its aim is to gain a comprehensive understanding of fraud in the banking sector and explore effective detection techniques. The paper examines advanced techniques such as data analysis, automatic learning algorithms, and real-time monitoring systems to detect suspicious patterns, anomalies, and deviations from normal behavior with precision. …”
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Detection of Objects Buried in the Sea Bottom with the Use of Parametric Echosounder by Eugeniusz KOZACZKA, Grazyna GRELOWSKA, Sławomir KOZACZKA, Wojciech SZYMCZAK

“…The paper contains results of a in situ research main task of which was to detect objects buried, partially or completely, in the sea bottom. …”
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Exploring the Role of Artificial Intelligence in Detecting Advanced Persistent Threats by Pedro Ramos Brandao

“…This paper explores the pivotal role of Artificial Intelligence (AI) in enhancing the detection and mitigation of APTs. By leveraging machine learning algorithms and data analytics, AI systems can identify patterns and anomalies that are indicative of sophisticated cyber-attacks. …”
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A Comprehensive Joint Learning System to Detect Skin Cancer by Lubna Riaz, Hafiz Muhammad Qadir, Ghulam Ali, Mubashir Ali, Muhammad Ahsan Raza, Anca D. Jurcut, Jehad Ali

“…This research offers a joint learning system using Convolutional Neural Networks (CNN) and Local Binary Pattern (LBP) followed by its concatenation of all the extracted features through CNN and LBP architecture. …”
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Volatility characteristics and hyperspectral-based detection models of diesel in soils by Jihye Shin, Jaehyung Yu, Jihee Seo, Lei Wang, Hyun-Cheol Kim

“…This study developed an efficient method using hyperspectral camera for detecting diesel content in soils with spectral indices. …”
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Deep learning-based edge detection for random natural images by Kanija Muntarina, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin

“…Edge detection plays a critical role in computer vision, particularly in the analysis of random natural images. …”
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Few-shot learning for novel object detection in autonomous driving by Yifan Zhuang, Pei Liu, Hao Yang, Kai Zhang, Yinhai Wang, Ziyuan Pu

“…Additionally, we design a one-stage object detector for efficient object detection in autonomous driving scenarios. Experiments on a self-driving dataset augmented with rare objects alongside the popular few-shot object detection (FSOD) benchmark, the pattern analysis, statical modeling, and computational learning PASCAL Visual Object Classes (PASCAL-VOC), demonstrate state-of-the-art accuracy in rare categories and superior inference speed compared to alternative algorithms. …”
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Detection and characteristic analysis of the crustal basement interface in Guangxi, China by Zhongxu Lu, Fuqiang Yang, Yang Yang, Haizhi Liao, Yajun Mo

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Fault Detection and Classification of Power Plant Using Neural Networks by Rawaa J. Hussein, Khalaf S. Gaeid, Amin Al-Habaibeh

“…The ANN can perform a wide range of tasks, including pattern recognition, classification, matching, prediction, decision-making, and control; hence, it was selected for this work. …”
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On the Development of New Forensic Tools for Detection of Human Skin Prints by V. A. Vasil’ev, T. A. Ermakova, Yu. A. Druzhinin, I. B. Afanas’ev, Yu. T. Yudina

“…The authors propose new model compositions of fingerprint powders considering the reviewed common patterns: non-magnetic and luminescent magnetic. The features of prints bearing surfaces and developed fingerprint powders have been evaluated by applying electronic microscopy methods (scanning and probe microscopy). …”
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Fatigue Detection of Air Traffic Controllers Through Their Eye Movements by Yi Hu, Haoran Shen, Hui Pan, Wenbin Wei

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Anomaly detection research using Isolation Forest in Machine Learning by A. S. Kechedzhiev, O. L. Tsvetkova

“…The study is devoted to assessing the applicability of the Isolation Forest method in the task of detecting anomalies in network traffic data characterized by insufficient markup. …”
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A Comprehensive Investigation of Fraud Detection Behavior in Federated Learning by Sun Rui

“…This research delves into the application of Federated Learning (FL) models for detecting fraud across different financial bodies. …”
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Detection of Southern Hemisphere Constellations Using Convolutional Neural Networks by Vladimir Riffo, Sebastian Flores, Eduardo Chuy-Kan, Victor Ariza

“…This neural network is widely known for its accuracy in object detection and is ideal for pattern recognition, such as constellations. …”
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Bibliometric Insights into Advances in Nondestructive Testing Techniques for Delamination Detection by Abdulwahd, Abdulrazaq. K., Mugisha, Simon, Chavula, Petros, Kayusi, Fredrick

“…Using advanced bibliometric methods and the biblioshiny package in R, the analysis evaluates annual scientific production, citation trends, thematic focus, and collaboration patterns. The results reveal a peak in research output in 2024, followed by a marked decline in 2025, alongside a steady decrease in average citations per article. …”
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Detection of Plants Leaf Diseases using Swarm Optimization Algorithms by Saud Abdul Razzaq, Baydaa Khaleel

“…Classification is widely and largely used in data analysis, and pattern recognition. The data analysis aims to discover similarities between them and group them based on similarity into multiple classes. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. …”
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Profiling antivaccination channels in Telegram: early efforts in detecting misinformation by Aelita Skarzauskiene, Monika Maciuliene, Aiste Dirzyte, Gintare Guleviciute

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