Evaluation of the Performance of Unsupervised Learning Algorithms for Intrusion Detection in Unbalanced Data Environments by Gutierrez-Portela Fernando, Almenares Mendoza Florina, Calderon-Benavides Liliana

“…Algorithms such as K-means++, DBSCAN, Local Outlier Factor (LOF), and Isolation Forest (I-forest) were analyzed using metrics like purity, homogeneity, completeness, V-measure, and adjusted mutual information to assess their effectiveness in detecting attacks such as DDoS, DoS, and reconnaissance. …”
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Thyroid hormone resistance syndrome: Prenatal detection and postnatal management in a newborn by Beatriz Parreira de Andrade, Marta Barbosa, Patrícia Tavares, Maria Adriana Rangel, Rosa Arménia Campos

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A Two-Stage YOLOv5s–U-Net Framework for Defect Localization and Segmentation in Overhead Transmission Lines by Aohua Li, Dacheng Li, Anjing Wang

“…Transmission-line defect detection is crucial for grid operation. Existing methods struggle to balance defect localization and fine segmentation. …”
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WCS-YOLOv8s: an improved YOLOv8s model for target identification and localization throughout the strawberry growth process by Sheng Gao, Sheng Gao, Gongpei Cui, Qiaohua Wang

“…This model can meet the demand for online real-time target identification and localization of strawberries and provide a new detection method for the automated monitoring and management of the whole growth process of strawberries.…”
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Predictors of the efficacy of intraoperative radiotherapy in organ-preserving treatment of early breast cancer by N. A. Alaichiev, E. A. Usynin, A. V. Doroshenko, I. V. Kondakova, E. Yu. Garbukov, E. E. Sereda, Zh. A. Startseva, M. A. Vostrikova, A. G. Ivanova

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Genome-wide analysis of Collo Nudo Italiana and Millefiori Piemontese local chicken breeds: genetic variability and structure analysis in the context of Italian chicken biodiversit... by Francesco Perini, Filippo Cendron, Cesare Castellini, Nicolaia Iaffaldano, Margherita Marzoni, Arianna Buccioni, Dominga Soglia, Achille Schiavone, Silvia Cerolini, Emiliano Lasagna, Martino Cassandro, Mauro Penasa

“…This study aimed to assess the genetic diversity and population structure of two Italian local chicken breeds, Millefiori Piemontese (PMP) and Collo Nudo Italiana (PCI), using the 600K Affymetrix SNP chip array, and to contextualise these breeds in the national biodiversity landscape based on 23 Italian local chicken breeds previously characterised. …”
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GU-Net3+: A Global-Local Feature Fusion Algorithm for Building Extraction in Remote Sensing Images by Yali Liu, Cui Ni, Peng Wang, Dongqing Yang, Hexin Yuan, Chao Ma

“…In this study, we propose a building detection method that integrates global and local features. …”
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Reduced crowding and poor contour detection in schizophrenia are consistent with weak surround inhibition. by Valentina Robol, Marc S Tibber, Elaine J Anderson, Tracy Bobin, Patricia Carlin, Sukhwinder S Shergill, Steven C Dakin

“…<h4>Background</h4>Detection of visual contours (strings of small oriented elements) is markedly poor in schizophrenia. …”
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HTC-HAD: A Hybrid Transformer-CNN Approach for Hyperspectral Anomaly Detection by Minghua Zhao, Wen Zheng, Jing Hu

“…This local perception constrains models from fully capturing intrinsic spatial&#x2013;spectral connections. …”
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Extraction and analysis of spatial heterodyne potassium signals based on principal component analysis and non-local means method by Wang XinQiang, Yang SiQian, Xiong Wei, Wang FangYuan, Ye Song

“…To probe into new methods for detecting flying targets, a spatial heterodyne spectrometer is utilized to detect the weak signals from potassium salt combustion against a sky background, combined with data processing techniques. …”
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Hybrid optimization driven fake news detection using reinforced transformer models by Ganesh Karthik M, Khadri Syed Faizz Ahmad, Sai Geetha Pamidimukkala, Asha Prashant Sathe, Sirisha G.N.V.G, Sitha Ram M, Koteswararao Ch

“…Abstract The large-scale production of multimodal fake news, combining text and images, presents significant detection challenges due to distribution discrepancies. …”
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Multi-granularity representation learning with vision Mamba for infrared small target detection by Yongji Li, Luping Wang, Shichao Chen

“…The fusion of contextual information and local feature achieves precise localization of small targets. …”
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Digits Recognition for Arabic Handwritten through Convolutional Neural Networks, Local Binary Patterns, and Histogram of Oriented Gradients by Bushra Mahdi Hasan, Zahraa Jasim Jaber, Ahmad Adel Habeeb

“…Specifically, the methods under consideration are Convolutional Neural Networks (CNNs), which have demonstrated their utility in diverse domains and offer effective solutions.  Local Binary Pattern (LBP) is a unique, efficient textural operator that finds widespread application in the area of computers such as biometric identification and detection of targets as feature extraction techniques. …”
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FedNDA: Enhancing Federated Learning with Noisy Client Detection and Robust Aggregation by Tuan Dung Kieu, Charles Fonbonne, Trung-Kien Tran, Thi-Lan Le, Hai Vu, Huu-Thanh Nguyen, Thanh-Hai Tran

“…To address this problem, this paper introduces a Federated learning framework with Noisy client Detection and robust Aggregation, FedNDA. In the first stage, FedNDA detects noisy clients by analyzing the distribution of their local losses. …”
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Mobility model detection method based on birth and death model in DTN environment by ENGGuang-hong D, AOWan-hua C, HANGJian Z, HENGXiong C, ENGLi F

“…A mobility model detection method based on birth and death model (MMD-BDM) in DTN environment was proposed.It first computed the connected channel capacity of sampling times according to the data traffic during the data transfer process,and then constructed the time varying intercommunication metrics at local,which composed of channel capacity between local node and others.Based on these,the connection birth and death mode of nodes based on connected edges was deduced,and then the birth and death features of the connected nodes was analyzed to detect the mobility model,which used to improve the routing strategy during the packages deliver process.Ultimately,the mobility model detection method was put into use in spray and wait routing (SWR) method and random network coding routing (RNCR) method to experiment,the simulation results show that,it can improve the opportunity routing performance of the data deliver rate and transfer latency in DTN environment.…”
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Image Edge Detection Based on Gaussian Mixture Model in Nonsubsampled Contourlet Domain by Li Yang, Chang Xia, Chang Juan

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Evaluation of Global-Scale and Local-Scale Optimized Segmentation Algorithms in GEOBIA With SAM on Land Use and Land Cover by Tao He, Jianyu Chen, Linchong Kang, Qiankun Zhu

“…This study investigates seven segmentation algorithms: mean shift (MF), O Sistema de Processamento de informa&#x00E7;&#x00F5;es georreferenciadas (the geographic information and image processing system) (SPRING), Estimation of scale parameter 2 (ESP2) (three global-scale algorithms), image object detection approach (IODA), SA, edge-guided image object detection approach (EIODA) (three local-scale optimization algorithms), and segment anything model (SAM) (deep learning). …”
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MOVING OBJECT DETECTION USING DISCRETE COSINE TRANSFORM BASED BACKGROUND SUBTRACTION by Sharmistha Puhan, Sambit Kumar Mishra, Deepak Kumar Rout

“…This article addresses the problem of visual detection of moving objects in bad weather conditions. …”
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Anterior Cruciate Ligament (ACL) Tear Detection Using Hybrid CNN Transformer by Suthir Sriram, Deependra K. Singh, D. V. Sairam, Nivethitha Vijayaraj, Thangavel Murugan

“…Next, it uses a selective scanning module to implement depth separable convolution using Selective Scanning Module (SS2D) to achieve a larger distance of the receptive field therefore increasing the chances of getting important long-distance connections and essential fine details for the tear detection process. A hybrid model is utilized that integrates these hybrid features and after global feature modeling, attempts to enhance both local and global information representation. …”
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Single-Frame Infrared Target Detection Based on Fast Content-Related Modeling by Zipeng Zhang, Xidong Zhao, Wenzheng Wang, Yuqi Han, Chenwei Deng, Zhuokai Li, Linbo Tang

“…Most of methods mainly concentrate on modeling global features, overlooking the variations in local features due to complex scenes. To solve these problems, a single-frame infrared target detection method based on fast content-related modeling is proposed to combine global and local features of infrared images, describing the common features of varying scenes robustly and enhancing the distinction between targets and backgrounds. …”
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