Features of the morphofunctional state of parotid salivary glands in six-month-old rats with experimentally induced fetal macrosomia by O. V. Garmash, H. I. Gubina-Vakulyk, David Vondrášek

“…The paper aims at studying the features of the morphofunctional state of parotid gland tissue in six-month-old rats born with induced macrosomia in its different variations. …”
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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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Introducing the Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integral Equations of the Volterra Type: Mathematical Methodology and Illustrative Applica... by Dan Gabriel Cacuci

“…Using a single large-scale (adjoint) computation, the 1st-FASAM-NIE-V enables the most efficient computation of the exact expressions of all first-order sensitivities of the decoder response to the feature functions and also with respect to the optimal values of the NIE-net’s parameters/weights after the respective NIE-Volterra-net was optimized to represent the underlying physical system. …”
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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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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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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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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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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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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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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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DualCMNet: a lightweight dual-branch network for maize variety identification based on multi-modal feature fusion by Xinhua Bi, Hao Xie, Ziyi Song, Jinge Li, Chang Liu, Xiaozhu Zhou, Helong Yu, Chunguang Bi, Ming Zhao

“…Additionally, existing multimodal methods face high computational complexity, making it difficult to balance accuracy and efficiency.MethodsBased on multi-modal data from 11 maize varieties, this paper presents DualCMNet, a novel dual-branch deep learning framework that utilizes a one-dimensional convolutional neural network (1D-CNN) for hyperspectral data processing and a MobileNetV3 network for spatial feature extraction from images. …”
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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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MSF-ACA: Low-Light Image Enhancement Network Based on Multi-Scale Feature Fusion and Adaptive Contrast Adjustment by Zhesheng Cheng, Yingdan Wu, Fang Tian, Zaiwen Feng, Yan Li

“…To address the issues of loss of important detailed features, insufficient contrast enhancement, and high computational complexity in existing low-light image enhancing methodologies, this paper presents a low-light image enhancement network (MSF-ACA), which uses multi-scale feature fusion and adaptive contrast adjustment. …”
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Ghost-Attention-YOLOv8: Enhancing Rice Leaf Disease Detection with Lightweight Feature Extraction and Advanced Attention Mechanisms by Thanh Dang Bui, Tra My Do Le

“…The Ghost model optimizes feature extraction by reducing computational complexity, while the attention modules enable the model to focus on relevant regions, improving detection performance. …”
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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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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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