MEP-YOLOv5s: Small-Target Detection Model for Unmanned Aerial Vehicle-Captured Images by Shengbang Zhou, Song Zhang, Chuanqi Li, Shutian Liu, Dong Chen

“…This model demonstrates an excellent performance in handling typical drone detection scenarios, especially for small and dense objects. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…This paper designed a scheduling framework based on cloud edge multi-data warehouses, integrated the query cost prediction model with machine learning technology as the core, and realized cloud edge collaborative execution and cloud edge selective execution on multiple query granularity, so as to improve the performance and query efficiency of the whole system. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…This paper designed a scheduling framework based on cloud edge multi-data warehouses, integrated the query cost prediction model with machine learning technology as the core, and realized cloud edge collaborative execution and cloud edge selective execution on multiple query granularity, so as to improve the performance and query efficiency of the whole system. …”
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CNN Assisted Dual Reservoir Hybrid Network for Power Consumption Forecasting by Hammad I. Sherazi, Omar Alrumayh, Shabana Habib, Abdulrahman Alsafrani, Muhammad Islam, Hedi A. Guesmi

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Development of a risk model for predicting cervical lymph node metastasis in major salivary gland carcinomas utilizing clinicopathological and ultrasound features by Huan-Zhong Su, Ji-Chao Lin, Long-Cheng Hong, Yu-Hui Wu, Feng Zhang, Kun Yu, Xiao-Dong Zhang, Zuo-Bing Zhang

“…Our aim is to develop a risk model that incorporates clinicopathological and ultrasound (US) features to predict the cervical lymph node metastasis (CLNM) in MSGCs. …”
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Smartphone-Based SPAD Value Estimation for Jujube Leaves Using Machine Learning: A Study on RGB Feature Extraction and Hybrid Modeling by Qi Wang, Ziyan Shi, Kaiyao Hou, Ning Yan, Cuiyun Wu, Xu Li

“…Among them, the CNN-SVR model showed the most stable performance with R² values of 72.21% and 77.44% on the training and validation sets, respectively, which outperformed the other models. …”
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Efficient deep learning model for classifying lung cancer images using normalized stain agnostic feature method and FastAI-2 by Pranshu Saxena, Sanjay Kumar Singh, Mamoon Rashid, Sultan S. Alshamrani, Mrim M. Alnfiai

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Leverage Gaussian Interpolation Features Extraction and Advanced Encode–Decode Models for 2D Steady State Flows Estimation by Thi-Thu-Huong Le, Changwoo Choi, Junyoung Son, Howon Kim

“…This paper introduces a novel approach that combines Gaussian interpolation-based feature extraction with advanced encode-decode models, including AutoEncoder, UNet, and DeepLabV3+. …”
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Multi-Step Peak Passenger Flow Prediction of Urban Rail Transit Based on Multi-Station Spatio-Temporal Feature Fusion Model by Jianan Sun, Xiaofei Ye, Xingchen Yan, Tao Wang, Jun Chen

“…In this paper, in order to solve this challenge, the Bi-graph Graph Convolutional Spatio-Temporal Feature Fusion Network (BGCSTFFN)-based model is introduced to capture complex spatio-temporal correlations. …”
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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification by Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Lu Peng, Fahdah Almarshad

“…While the pre-trained models showed good classification performance, they struggled to classify remote-sensing images with high precision accurately. …”
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A Wind Power Density Forecasting Model Based on RF-DBO-VMD Feature Selection and BiGRU Optimized by the Attention Mechanism by Bixiong Luo, Peng Zuo, Lijun Zhu, Wei Hua

“…Accurate prediction of wind power density (WPD) holds significant practical importance for wind farms, grid operators, and the entire wind power industry, as it facilitates informed decision-making, optimized resource allocation, and enhanced system performance. This paper proposes a novel WPD forecasting model based on RF-DBO-VMD feature selection and BiGRU optimized by an attention mechanism. …”
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Feature Extraction and Attribute Recognition of Aerosol Particles from In Situ Light-Scattering Measurements Based on EMD-ICA Combined LSTM Model by Heng Zhao, Yanyan Zhang, Dengxin Hua, Jiamin Fang, Jie Zhang, Zewen Yang

“…Then, the wavelet scattering network is used to realize the adaptive extraction of the characteristics of the particle light-scattering signal, and the Bayesian Optimization model is used to optimize the hyperparameters of the LSTM neural network. …”
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Development and Validation of Predictive Models for Differentiating Resectable Stage III Peripheral SCLC from NSCLC Using Radiomic Features and Clinical Parameters by Junjie Zhang MD, Ligang Hao MD, Qiuxu Zhang MD, Lina Zheng MD, Qian Xu PhD, Fengxiao Gao MD

“…The cohort was divided into a training set (n = 92) and a test set (n = 40). Radiomic feature selection was performed using the LASSO algorithm, and nine machine learning models were evaluated. …”
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Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems by Maham Nayab, Asim Waris, Muhammad Jawad Khan, Dokhyl AlQahtani, Ahmed Imran, Syed Omer Gilani, Umer Hameed Shah

“…Using the best-performing features, all possible sets of 2, 3, 4 and 5 features were tested, and the 5-feature set exhibited the best performance. …”
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FTT: A Frequency-Aware Texture Matching Transformer for Digital Bathymetry Model Super-Resolution by Peikun Xiao, Jianping Wu, Yingjie Wang

“…TMB improves fidelity of generated HR DBM by generating position offsets to restore warped textures in deep features. Experimental results have demonstrated that the proposed FTT has superior performance in terms of elevation, slope, aspect, and fidelity of generated HR DBM. …”
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Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder by Elahe Hosseini, Seyyed Ali Hosseini, Stijn Servaes, Brandon Hall, Pedro Rosa-Neto, Ali-Reza Moradi, Ajay Kumar, Mir Mohsen Pedram, Sanjeev Chawla

“…<b>Results:</b> A 10-fold cross-validation test revealed that the LSTM model, which incorporated both MRI data and personal attributes, had the best diagnostic performance among all tested models in the diagnosis of ADHD with an accuracy of 0.86 and area under the receiver operating characteristic (ROC) curve (AUC) score of 0.90. …”
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Single-cell transcriptomics and machine learning unveil ferroptosis features in tumor-associated macrophages: Prognostic model and therapeutic strategies for lung adenocarcinoma by Ting Ji, Ting Ji, Juanli Jiang, Juanli Jiang, Xin Wang, Xin Wang, Kai Yang, Kai Yang, Shaojin Wang, Shaojin Wang, Bin Pan, Bin Pan

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Development of a Nomogram Model to Predict Mortality in ANCA‐Associated Vasculitis Patients With Pulmonary Involvement by Qifang Guo, Yijia Shao, Le Yu, Xiuling Zhang, Jingjing Shang, Xueqin Feng, Wei Zhou, Xinwang Duan

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Emo-SL Framework: Emoji Sentiment Lexicon Using Text-Based Features and Machine Learning for Sentiment Analysis by Manar Alfreihat, Omar Saad Almousa, Yahya Tashtoush, Anas AlSobeh, Khalid Mansour, Hazem Migdady

“…This research aims to develop an Emoji Sentiment Lexicon (Emo-SL) tailored to Arabic-language tweets and demonstrate performance improvements by combining emoji-based features with machine learning (ML) for sentiment classification. …”
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A Novel Temporal Footprints-Based Framework for Fake News Detection by Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Ashok Kumar Das, Shehzad Ashraf Chaudhry

“…Later, the temporal features are combined with the textual features to increase classifier performance. …”
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