Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring by Ruipu Ji, Shokrullah Sorosh, Eric Lo, Tanner J. Norton, John W. Driscoll, Falko Kuester, Andre R. Barbosa, Barbara G. Simpson, Tara C. Hutchinson

“…A feature point tracking-based algorithm for square checkerboard patterns and a Hough Transform-based algorithm for concentric circular patterns are developed to ensure reliable detection and tracking of image features. …”
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A Smart Web-Based Power Quality and Energy Monitoring System With Enhanced Features by Rami Moustafa, Hussain Shareef, Madathodika Asna, Rachid Errouissi, Jeyraj Selvaraj

“…The PQEm device includes time-frequency analysis to enhance visualization and characterization of voltage and current data. …”
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Thyroglobulin-to-tumor volume ratio combined with ultrasound features for diagnosing thyroid follicular neoplasms by Xixi Zhu, Xixi Zhu, Fen Liu, Jiaye Liu, Jiaye Liu, Zhihui Li, Yu Ma

“…The combined diagnostic model incorporating Tg/Vol ratio and CEUS features significantly improves FTC detection accuracy.…”
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Features of Bearing on Underwater Object Using Phase Information of a Differential Stereo Sensor by V. A. Shirokov, A. I. Bazhenova, V. N. Milich

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Features of the functional state of the enteropancreatic hormonal system in pregnant women with gestational diabetes mellitus by F. O. Ushanova, T. Y. Demidova, T. N. Korotkova

“…Korotkova21Pirogov Russian National Research Medical University, Moscow, Russia2Federal Research Centre of Nutrition, Biotechnology and Food Safety, Moscow, RussiaBACKGROUND: The prevalence of gestational diabetes mellitus (GDM) is growing rapidly, along with which the typical portrait of a pregnant woman with this disease is changing. Frequent detection of GDM in the early stages of pregnancy causes a high interest in the study of new mechanisms of its development.AIM: Evaluation of the state of the incretin response based on the analysis of the secretion of GLP-1, glucagon, insulin and c-peptide in pregnant women with different periods of GDM development.MATERIALS AND METHODS: A single-center prospective comparative uncontrolled study that included pregnant women with GSD, divided into 2 groups depending on the duration of the disease: group 1 — pregnant women who were diagnosed at <24 weeks of gestation (n=65), group 2 — at ≥24 weeks of gestation (n=26). …”
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An explainable EEG epilepsy detection model using friend pattern by Turker Tuncer, Sengul Dogan

“…EEG signals have commonly been used to detect epilepsy. Therefore, the main objective of this research is to demonstrate the epilepsy detection capability of the presented new-generation relation-centric feature extraction function. …”
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Clinical and histopathological features of lupus nephritis and the risk of long-term kidney outcomes in Indonesia by Ni Made Hustrini, Ni Made Hustrini, Endang Susalit, Monik Ediana Miranda, Meilania Saraswati, Y. K. Onno Teng, Merel van Diepen, Joris I. Rotmans

“…A linear mixed-model analysis was performed to assess the association between lupus nephritis class and kidney function decline.ResultsThis study included 268 patients, with a mean age of 28.7 + 8.5 years, and 94.8% were female. …”
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TATPat based explainable EEG model for neonatal seizure detection by Turker Tuncer, Sengul Dogan, Irem Tasci, Burak Tasci, Rena Hajiyeva

“…In this EFE model, there are four essential phases and these phases: (i) automaton and transformer-based feature extraction, (ii) feature selection deploying cumulative weight-based neighborhood component analysis (CWNCA), (iii) the Directed Lobish (DLob) and Causal Connectome Theory (CCT)-based explainable result generation and (iv) classification deploying t algorithm-based support vector machine (tSVM). …”
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Detection of axonal synapses in 3D two-photon images. by Cher Bass, Pyry Helkkula, Vincenzo De Paola, Claudia Clopath, Anil Anthony Bharath

“…Studies of structural plasticity in the brain often require the detection and analysis of axonal synapses (boutons). …”
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Transformer Self-Attention Change Detection Network with Frozen Parameters by Peiyang Cheng, Min Xia, Dehao Wang, Haifeng Lin, Zikai Zhao

“…These results fully demonstrate the superiority, robustness, and generalization ability of ZAQNet in change detection tasks and provide an efficient and reliable solution for remote sensing image analysis.…”
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Different features of acute myeloid leukemia stem cell quantification in intensively treated patients by Lok Lam Ngai, Tom Reuvekamp, Diana Hanekamp, Fleur Janssen, Laura Oudshoorn-van Marsbergen, Jannemieke Carbaat-Ham, Maaike A.M. Hofland, Mona M.H.E. Fayed, Angèle Kelder, Willemijn J. Scholten, Alexander N. Snel, Costa Bachas, Jesse M. Tettero, Dimitri A. Breems, Thomas Fischer, Bjørn T. Gjertsen, Laimonas Griškevičius, Gunnar Juliusson, Arjan A. van de Loosdrecht, Johan A. Maertens, Markus G. Manz, Thomas Pabst, Jakob R. Passweg, Kimmo Porkka, Peter J.M. Valk, Patrycja Gradowska, Bob Löwenberg, Gert J. Ossenkoppele, David C. de Leeuw, Jacqueline Cloos

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Clinical Findings Associated with a De Novo Partial Trisomy 10p11.22p15.3 and Monosomy 7p22.3 Detected by Chromosomal Microarray Analysis by Omid Kohannim, Jane Peredo, Katrina M. Dipple, Fabiola Quintero-Rivera

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Novel Machine Learning-Based Brain Attention Detection Systems by Junbo Wang, Song-Kyoo Kim

“…The results of our analysis on a publicly available dataset indicate that KNN with the feature importance feature extraction method performed the best, achieving 99.56% accuracy, 99.67% recall, and 99.44% precision with a rapid training time.…”
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YOLOv8 with Post-Processing for Small Object Detection Enhancement by Jinkyu Ryu, Dongkurl Kwak, Seungmin Choi

“…Small-object detection in images, a core task in unstructured big-data analysis, remains challenging due to low resolution, background noise, and occlusion. …”
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Multitask semantic change detection guided by spatiotemporal semantic interaction by Yinqing Wang, Liangjun Zhao, Yueming Hu, Hui Dai, Yuanyang Zhang

“…To further enhance detection performance, a dynamic depthwise separable convolution is designed in the CTIM module, which can adaptively adjust convolution kernels to more precisely capture change features in different regions of the image. …”
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Hyperspectral target detection based on graph sampling and aggregation network. by Tie Li, Hongfeng Jin, Zhiqiu Li

“…It achieves this by extracting feature vectors through principal component analysis to construct adjacency matrices and performing convolution operations on hyperspectral images via sparse matrix multiplication, which enables the propagation and aggregation of node features within the graph structure. …”
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Integrating SNP data to reveal the adaptive selection features of goat populations in extreme environments by Wannian Wang, Ke Cai, Mengdan Fan, Zhixu Pang, Yangyang Pan, Lifen Cheng, Liying Qiao, Ruizhen Wang, Wenzhong Liu, Jianhua Liu

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Features of the daily blood pressure in patients with ischemic chronic heart failure and renal dysfunction by V. D. Syvolap, D. A. Lashkul

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Image Target Detection and Recognition Method Using Deep Learning by Hongyan Sun

“…Based on the analysis of the existing theories of deep learning detection and recognition, this paper summarized the composition and working principle of the traditional image target detection and recognition system and compared the basic models of target detection and recognition, such as R-CNN network, Fast-RCNN network, and Faster-RCNN network. …”
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Anomaly Detection for Suspension Systems Based on the Gaussian Distribution of Hyperspheres by Ping WANG, Zi MEI, Zhiqiang LONG

“…Then, the abnormal threshold was determined according to the Euclidean distance between the sample feature and the center of the sphere. The experimental results of the field data show that, compared with the methods based on empirical threshold, the principal component analysis (PCA) and support vector data description (SVDD), the proposed method is more superior in anomaly detection ability.…”
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