Reinforcement Learning-Based Generative Security Framework for Host Intrusion Detection by Yongsik Kim, Su-Youn Hong, Sungjin Park, Huy Kang Kim

“…Attackers create more complicated attack patterns and configure attack behavior to resemble normal behavior to evade detection by defenders. …”
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Dual Transformers With Latent Amplification for Multivariate Time Series Anomaly Detection by Yeji Choi, Kwanghoon Sohn, Ig-Jae Kim

“…Transformer-based reconstruction methods have recently shown strong performance but often suffer from overgeneralization, where anomalies are reconstructed too accurately, thereby reducing the separability between normal and abnormal patterns. Prior works have attempted to mitigate this by incorporating two-stage frameworks or external memory modules to explicitly store normal patterns and amplify deviations from abnormal patterns. …”
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Contextual information based anomaly detection for multi-scene aerial videos by Girisha S, Ujjwal Verma, Manohara M M. Pai, Radhika M. Pai

“…In this regard, the present work proposes a novel multi-scene aerial video anomaly detection dataset with frame-level annotations. In addition, a novel Computer Aided Decision (CAD) support system is proposed to analyze and detect anomalous patterns from UAV-based surveillance videos. …”
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Detection and location of EEG events using deep learning visual inspection. by Mohammad Amin Fraiwan

“…This signal contains a number of distinctive waveform patterns that reflect the subject's health state in relation to sleep, neurological disorders, memory functions, and more. …”
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“No End Point Detected”: A Unique Coagulation Profile Unmasking Dysfibrinogenemia by Kelsey Uminski, Xiu Yan Jiang

“…This pattern should prompt consideration of profound hypofibrinogenemia or qualitative fibrinogen defects. …”
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Amplitude-integrated electroencephalography for neonatal seizure detection. An electrophysiological point of view by Sebastián Gacio

“…Its main value lies in the relative simplicity of interpretation, allowing nonspecialist members of the care team to engage in real-time detection of electrographic seizures. Nevertheless, to avoiding misdiagnosing rhythmic artifacts as seizures, it is necessary to recognize the electrophysiological ictal pattern in the conventional EEG trace available in current devices. …”
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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…In this work, we propose a Random Forest-based event classification algorithm designed to handle the unique patterns of vibration and acceleration data in road event detection for an urban traffic scenario. …”
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Automatic gait EVENT detection in older adults during perturbed walking by Shuaijie Wang, Kazi Shahrukh Omar, Fabio Miranda, Tanvi Bhatt

“…The results highlight the efficacy of kinematic approaches, demonstrating their potential in gait event detection for clinical settings. When integrated with wearable sensors or computer vision techniques, these methods enable real-time, precise monitoring of gait patterns, which is helpful for applying personalized programs for fall prevention. …”
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The Evolution of Computer-assisted Detection of Pulmonary Embolism from Volume to Voxel by Condrea Florin, Rapaka Saikiran, Itu Lucian, Leordeanu Marius

“…The evolution of computer-assisted detection (CAD) for PE has transformed dramatically over the past decades, progressing from simple pattern recognition to sophisticated deep learning approaches. …”
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A Tunnel Surface Diseases Detection Algorithm Based on YOLOv4 by LI Jia, QIU Xinhua, JI Yuwen

“…Aiming at the problem that tunnel environment is complex and variable and the contrast of surface image is low, which makes the traditional pattern recognition method cannot effectively detect diseases. …”
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BCAST IDS: A Novel Network Intrusion Detection System for Broadcast Networks by Javier Gombao

“…This study introduces a novel and lightweight NIDS called Broadcast IDS (BCAST IDS) that uses specific network traffic patterns and the Isolation Forest algorithm to detect anomalies in broadcast networks. …”
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Machine Learning-Based Network Anomaly Detection: Design, Implementation, and Evaluation by Pilar Schummer, Alberto del Rio, Javier Serrano, David Jimenez, Guillermo Sánchez, Álvaro Llorente

“…<b>Background:</b> In the last decade, numerous methods have been proposed to define and detect outliers, particularly in complex environments like networks, where anomalies significantly deviate from normal patterns. …”
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High-Level Codewords Based on Granger Causality for Video Event Detection by Shao-nian Huang, Dong-jun Huang, Mansoor Ahmed Khuhro

“…Video event detection is a challenging problem in many applications, such as video surveillance and video content analysis. …”
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Novel approach for detection of cell antigen coexpression using immunological biochip by A. V. Shishkin, N. G. Ovchinina, S. S. Bessmeltsev

“…Results are compared with data of investigation where previously known patterns of biochips were used.…”
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Industrial Image Anomaly Detection via Synthetic-Anomaly Contrastive Distillation by Junxian Li, Mingxing Li, Shucheng Huang, Gang Wang, Xinjing Zhao

“…<i>FeaCali</i> modules are trained to strip out a student’s anomalous patterns in anomaly branches, enhancing the student network’s exclusive modeling of normal patterns. …”
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Leveraging U-Net and ASPP for effective fault detection in photovoltaic modules by Khalfalla Awedat, Masoud Alajmi, Mustafa Elfituri

“…These results highlight the effectiveness of incorporating region-specific dilation strategies, enhancing the model’s ability to detect diverse and challenging fault patterns in complex thermal imagery. …”
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Symmetry constrained neural networks for detection and localization of damage in metal plates by James Amarel, Christopher Rudolf, Athanasios Iliopoulos, John G. Michopoulos, Leslie N. Smith

“…The present paper is concerned with deep learning techniques applied to detection and localization of damage in a thin aluminum plate. …”
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Graph-Attention Diffusion for Enhanced Multivariate Time-Series Anomaly Detection by Vadim Lanko, Ilya Makarov

“…Multivariate time-series anomaly detection is a complex task that requires capturing temporal and spatial correlations. …”
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Deep Learning Based Breast Cancer Detection Using Decision Fusion by Doğu Manalı, Hasan Demirel, Alaa Eleyan

“…First, SVM distinguishes between different tumor types using local binary pattern (LBP) features. Second, a pre-trained CNN extracts features, and SVM identifies potential tumors. …”
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Detection of Inception Cavitation in Centrifugal Pump by Fluid-Borne Noise Diagnostic by Liang Dong, Yuqi Zhao, Cui Dai

“…This paper presents an experimental methodology that is capable of sensitively detecting the cavitation inception in a centrifugal pump. …”
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