Surface Eddy Current Probes: Excitation Systems of the Optimal Electromagnetic Field (Review) by V. Ya. Halchenko, R. V. Trembovetskaya, V. V. Tychkov

“…As a result, the classification of probes on a number of features that characterize the excitation systems was proposed.…”
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A fast and fully automated system for segmenting retinal blood vessels in fundus images by Alqassab Ans Ibrahim Mahameed, Luque-Nieto Miguel-Ángel

“…The problem of segmenting retinal blood vessels in fundus images arises from the challenges of accurately detecting and delineating vessels due to their complex structures, varying sizes, and overlapping features. …”
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Research Progress of Dangerous Driving Behavior Recognition Methods Based on Deep Learning by Junjian Hou, Bingyu Zhang, Yudong Zhong, Wenbin He

“…The precision of physiological detection depends on the quality of the equipment. …”
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A Portable Smartphone-Based 3D-Printed Biosensing Platform for Kidney Function Biomarker Quantification by Sangeeta Palekar, Sharayu Kalambe, Jayu Kalambe, Madhusudan B. Kulkarni, Manish Bhaiyya

“…Detecting kidney function biomarkers is critical for the early diagnosis of kidney diseases and monitoring treatment efficacy. …”
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Spatiotemporal prediction of soil organic carbon density in Europe (2000–2022) using earth observation and machine learning by Xuemeng Tian, Sytze de Bruin, Rolf Simoes, Mustafa Serkan Isik, Robert Minarik, Yu-Feng Ho, Murat Şahin, Martin Herold, Davide Consoli, Tomislav Hengl

“…The PI validation confirmed effective uncertainty estimation, though with reduced accuracy for higher SOCD values. Shapley analysis identified soil depth as the most influential feature, followed by vegetation, long-term bioclimate, and topographic features. …”
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Dual-Phase Severity Grading of Strawberry Angular Leaf Spot Based on Improved YOLOv11 and OpenCV by Yi-Xiao Xu, Xin-Hao Yu, Qing Yi, Qi-Yuan Zhang, Wen-Hao Su

“…In addition, this two-stage grading framework achieves an average accuracy of 94.2% in detecting selected strawberry horn leaf spot disease samples, providing real-time field diagnostics and a high-throughput phenotypic analysis for resistance breeding programs. …”
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Metabolomics of Papanicolaou Tests for the Discovery of Ovarian Cancer Biomarkers by Samyukta Sah, Elisabeth M. Schwiebert, Samuel G. Moore, Ying Liu, David A. Gaul, Kristin L. M. Boylan, Amy P. N. Skubitz, Facundo M. Fernández

“…Among these detected features, 453 unique lipids, representative of 20 different lipid subclasses, were annotated in all 29 samples. …”
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APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System by Safdar Hussain Javed, Maaz Bin Ahmad, Muhammad Asif, Waseem Akram, Khalid Mahmood, Ashok Kumar Das, Sachin Shetty

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U-Net-based VGG19 model for improved facial expression recognition by Xiaohu ZHAO, Jingyi ZHANG, Mingzhi JIAO, Lixun XIE, Lanfei WANG, Weiqing SUN, Di ZHANG

“…This adjustment ensures that important features are emphasized while redundant features are suppressed, streamlining the recognition process. …”
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Unraveling volatile metabolites in pigmented onion (Allium cepa L.) bulbs through HS-SPME/GC–MS-based metabolomics and machine learning by Kaiqi Cheng, Kaiqi Cheng, Jingzhe Xiao, Jingyuan He, Rongguang Yang, Jinjin Pei, Jinjin Pei, Wengang Jin, Wengang Jin, A. M. Abd El-Aty, A. M. Abd El-Aty

“…Additionally, 33 and 38 feature metabolites were selected by SelectKBest and LASSO, respectively. …”
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Investigation of the Effect of Tool Rotation Rate in EDM Drilling of Ultrafine Grain Tungsten Carbide Using Predictive Machine Learning by Sai Dutta Gattu, Lucas Pardo Bernardi, Jiwang Yan

“…While correlation analysis showed weak global associations, phase-dependent SHAP values revealed opposing feature effects, allowing the context-informed interpretation of model behavior. …”
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Remote Sensing Evaluation of Drought Effects on Crop Yields Across Dobrogea, Romania, Using Vegetation Health Index (VHI) by Cristina Serban, Carmen Maftei

“…The trend analysis results indicated a nonuniform spatial feature of the negative (drying)/positive (wetting) trends at the regional level, with statistically significant trends identified only over small areas. …”
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Methodology for Data Integration in 3D-HBIM Digital Models. Case Study: the Holy Chalice Chapel of Valencia Cathedral by Pablo Ariel Escudero, Concepción López González, Jorge Luis García Valldecabres

“…These algorithms play a crucial role in identifying and classifying points based on their geometry and chromatic characteristics. A key feature of the approach is the use of colorimetry-based classification, which detects significant changes in the RGB values of the points, thereby aiding in the identification of patterns and potential deterioration in construction materials.…”
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Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…To solve the problem that the parameter of silicon content ([Si]) in hot mental is difficult to be directly detected and obtained by manual analysis with large time delay, a method of sparse and robust least squares support vector regression (R-S-LS-SVR) was proposed to establish a dynamic model of[Si] with the help of the multi-objective genetic optimization of model parame-ters. …”
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Semantic HBIM for Heritage Conservation: A Methodology for Mapping Deterioration and Structural Deformation in Historic Envelopes by Enrique Nieto-Julián, María Dolores Robador, Juan Moyano, Silvana Bruno

“…Historic buildings often feature complex geometries and visible material traces of time, requiring detailed analysis. …”
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Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory by Zilong Zhao, Luliang Tang, Chang Ren, Xue Yang, Zihan Kan, Qingquan Li

“…The framework is divided into three parts: road traffic status acquisition, traffic anomaly detection, and urban anomaly analysis. First, we perform filtering and map matching on the trajectory data to obtain the traffic states of urban roads and construct them into a tensor. …”
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Multi-Spectral Optimization for Tissue Probing Using Machine Learning by Yarden Tzabari Kelman, Hadas Lupa Yitzhak, Nadav Shabairou, Shahaf Finder, Zeev Zalevsky

“…Using five wavelengths, 9 vibration frequencies and 19 signal analysis parameters, ex-vivo experiments were performed on porcine skin tissues and were analyzed using artificial intelligence tools which could detect the strong features for each wavelength individually. …”
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Efficient brain tumor grade classification using ensemble deep learning models by Sankar M, Baiju BV, Preethi D, Ananda Kumar S, Sandeep Kumar Mathivanan, Mohd Asif Shah

“…Abstract Detecting brain tumors early on is critical for effective treatment and life-saving efforts. …”
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Model and Variable Selection Procedures for Semiparametric Time Series Regression by Risa Kato, Takayuki Shiohama

“…Semiparametric regression models are very useful for time series analysis. They facilitate the detection of features resulting from external interventions. …”
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multiDGD: A versatile deep generative model for multi-omics data by Viktoria Schuster, Emma Dann, Anders Krogh, Sarah A. Teichmann

“…It shows outstanding performance on data reconstruction without feature selection. We demonstrate on several data sets from human and mouse that multiDGD learns well-clustered joint representations. …”
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