A novel speaker verification approach featuring multidomain acoustics based on the weighted city-block Minkowski distance by Khushboo Jha, Sumit Srivastava, Aruna Jain

“…The weighted city block Minkowski distance is proposed to compare reference and test speech templates. Parameters are computed based on the confusion matrix, template matching distance functions, dynamic acoustic conditions, and additive white Gaussian noise. …”
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FDRL: a data-driven algorithm for forecasting subsidence velocities in Himalayas using conventional and traditional soil features by Sahil Sankhyan, Ajoy Kumar, Praveen Kumar, Aaditya Sharma, K. V. Uday, Varun Dutt

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Definition of the Main Features of Material Assemblies for Thermal Protective Clothing During External High-temperature Effect Modelling by Nataliia Ostapenko, Marina Kolosnichenko, Larysa Tretiakova, Tatyana Lutsker, Kalina Pashkevich, Alla Rubanka, Halyna Tokar

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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…Experimental results highlight the superior performance of the LGBM classifier, achieving an impressive 99% accuracy, recall, f1, and precision score of 98% with a computational runtime of just 0.084 seconds. K-fold cross-validation ensured the robustness of the models, and optimization techniques were applied to fine-tune parameters for maximum accuracy. …”
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Predictive analysis of clinical features for HPV status in oropharynx squamous cell carcinoma: A machine learning approach with explainability by Emily Diaz Badilla, Ignasi Cos, Claudio Sampieri, Berta Alegre, Isabel Vilaseca, Simone Balocco, Petia Radeva

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XTNSR: Xception-based transformer network for single image super resolution by Jagrati Talreja, Supavadee Aramvith, Takao Onoye

“…The experimental results show better performance in Peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and visual quality than the state-of-the-art techniques. By optimizing parameters, the suggested architecture also lowers computational complexity. …”
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Generative AI for Bayesian Computation by Nick Polson, Vadim Sokolov

“…Generative quantile methods have a number of advantages over traditional approaches such as approximate Bayesian computation (ABC) or GANs. Primarily, quantile architectures are density-free and exploit feature selection using dimensionality reducing summary statistics. …”
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An Improved Ant Colony Optimization to Uncover Customer Characteristics for Churn Prediction by Ibrahim Al-Shourbaji, Abdoh Jabbari, Shaik Rizwan, Mostafa Mehanawi, Phiros Mansur, Mohammed Abdalraheem

“…Customer churn prediction is a critical task in the telecommunication (telecom) industry, where accurate identification of customers at risk of churning plays a vital role in reducing customer attrition. Feature selection (FS) is an integral part in Machine Learning (ML) models which aims to improve performance and reduce computational time (CT). …”
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Anatomical characteristics of the pubic symphysis of the second period of adulthood according to computer tomography data by I. A. Balandina, A. V. Klimets, A. A. Balandin

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Clinical, radiologic, and morphological diagnosis of hypersensitivity pneumonitis by A. L. Cherniaev, E. V. Kusraeva, M. V. Samsonova, S. N. Avdeev, N. V. Trushenko, E. L. Tumanova

“…Clinical symptoms, data of high-resolution computed tomography, parameters of external respiration, and histological changes in the lung tissue obtained via open and transbronchial biopsies were studied retrospectively in 175 patients with hypersensitivity pneumonitis (HP). …”
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Optimized DINO model for accurate object detection of sesame seedlings and weeds by Yong Wang, ShunFa Xu, ZhenYuan Ye, KongHao Cheng

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Flaw-YOLOv5s: A Lightweight Potato Surface Defect Detection Algorithm Based on Multi-Scale Feature Fusion by Haitao Wu, Ranhui Zhu, Hengren Wang, Xiangyou Wang, Jie Huang, Shuwei Liu

“…Firstly, Depthwise Separable Convolution (DWConv) is used to displace the original Conv in the YOLOv5s network, aiming to reduce computational burden and parameters. Then, the SPPF in the backbone network is replaced by SPPELAN, which combines SPP with ELAN to enable the model to perform multi-scale pooling and feature extraction, optimizing detection capacity for small targets in potatoes. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…The study focuses on developing a shallow model with deep feature extraction to bring down the computational load with reduced time for training without compromising on any performance parameters. …”
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Feature-Driven Density Prediction of Maraging Steel Additively Manufactured Samples Using Pyrometer Sensor and Supervised Machine Learning by Rajesh Kumar Balaraman, Shaista Hussain, John Kgee Ong, Qing Yang Tan, Nagarajan Raghavan

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An object detection model AAPW-YOLO for UAV remote sensing images based on adaptive convolution and reconstructed feature fusion by Yiming Wu, Xiaofang Mu, Hong Shi, Mingxing Hou

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LMAD-YOLO: A vehicle image detection algorithm for drone aerial photography based on multi-scale feature fusion. by Xue Xing, Fahui Luo, Le Wan, Kang Lu, Yuqi Peng, Xiujuan Tian

“…Adown module is introduced to replace the model of sampling, in order to reduce the parameters and computational complexity while enhancing the accuracy of small target detection. …”
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SFSIN: A Lightweight Model for Remote Sensing Image Super-Resolution with Strip-like Feature Superpixel Interaction Network by Yanxia Lyu, Yuhang Liu, Qianqian Zhao, Ziwen Hao, Xin Song

“…However, existing super-resolution methods are not applicable to resource-constrained edge devices because they are hampered by a large number of parameters and significant computational complexity. …”
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Advancing Glaucoma Diagnosis Through Multi‐Scale Feature Extraction and Cross‐Attention Mechanisms in Optical Coherence Tomography Images by Hamid Reza Khajeha, Mansoor Fateh, Vahid Abolghasemi, Amir Reza Fateh, Mohammad Hassan Emamian, Hassan Hashemi, Akbar Fotouhi

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Enhanced framework for credit card fraud detection using robust feature selection and a stacking ensemble model approach by Rahul Kumar Gupta, Asmaul Hassan, Samir Kumar Majhi, Nikhat Parveen, Abu Taha Zamani, Raju Anitha, Binayak Ojha, Abhinav Kumar Singh, Debendra Muduli

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Hybrid feature-time series neural network for predicting ACL forces in martial artists with resistive braces after reconstruction by Dongyue Li, Haojie Li, Yang Hang

“…The goal was to leverage time-series biomechanical parameters and static clinical features to optimize postoperative recovery strategies.MethodsA prospective cohort of 44 martial artists post-ACL reconstruction was randomized into an experimental group (EG, n = 22) using a resistive brace and a control group (CG, n = 22) using a traditional brace. …”
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