Enhancing Wind Turbine Efficiency: An Experimental Investigation of a Sensorless Three-Vector Finite Set Predictive Torque Control Approach for PMSG-Based Systems by Marouane Ahmed Ghodbane, Toufik Mohamed Benchouia, Mohamed Chebaani, Mohamed Becherif, Yassine Himeur, Amar Golea, Abdelmoumen Ghilani, Zakaria Alili, Shadi Atalla, Wathiq Mansoor

“…However, managing wind turbines efficiently and reliably is challenging, especially when wind conditions are unpredictable. …”
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HiDRA-DCDNet: Dynamic Hierarchical Attention and Multi-Scale Context Fusion for Real-Time Remote Sensing Small-Target Detection by Jiale Wang, Zhe Bai, Ximing Zhang, Yuehong Qiu, Fan Bu, Yuancheng Shao

“…Small-target detection in remote sensing presents three fundamental challenges: limited pixel representation of targets, multi-angle imaging-induced appearance variance, and complex background interference. …”
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Link Prediction in Social Networks Using the HTOA by Foad Asef, Vahid Majidnezhad, Mohammad-Reza Feizi-Derakhshi

“…Despite considerable advancements in this field, existing methods often face challenges related to computational efficiency and prediction accuracy. This study introduces a novel approach to link prediction in social networks by employing the Heat Transfer Optimization Algorithm (HTOA) for topological feature selection. …”
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RNA-BioLens: A Novel Raspberry Pi-Based Digital Microscope With Image Processing for Acute Lymphoblastic Leukemia Detection by Angeline Dwi Sanjaya, Rachmad Setiawan, Nada Fitrieyatul Hikmah

“…This system aims to enhance detection accuracy and speed while balancing complexity and procurement costs. …”
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Real-Time Detection and Instance Segmentation Models for the Growth Stages of <i>Pleurotus pulmonarius</i> for Environmental Control in Mushroom Houses by Can Wang, Xinhui Wu, Zhaoquan Wang, Han Shao, Dapeng Ye, Xiangzeng Kong

“…Challenges such as scene complexity and overlapping mushroom clusters can impact the accuracy of growth stage detection and target segmentation. …”
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Establishment and application of a rapid new detection method for antimicrobial susceptibility testing of Klebsiella pneumoniae based on MALDI-TOF MS by Yapei Zhang, Fanghua Fan, Xuan Wang, Jie Zhu, Shilei Dong

“…Current rapid AST techniques are hampered by factors such as high costs, technological complexities, and limited detection capabilities. We present a novel rapid method and applied to the determination of the susceptibility of K. pneumoniae to imipenem. …”
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Automatic Segmentation and Characterization of Structure Planes From Borehole Images Based on Deep Learning by Shuangyuan Chen, Zengqiang Han, Yi Cheng, Chao Wang

“…By providing a reliable and efficient tool for structure plane segmentation and parameter characterization, this study enhances the accuracy and efficiency of rock mass structure detection and analysis.…”
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Training a convolutional neural network for exoplanet classification with transit photometry data by Juliana Wang

“…As a result, efforts to enhance the efficiency of exoplanet research have led to the development of various detection methods, including transit photometry. …”
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Ensemble Deep Learning Models for Enhanced Brain Tumor Classification by Leveraging ResNet50 and EfficientNet-B7 on High-Resolution MRI Images by Retinderdeep Singh, Sheifali Gupta, Salil Bharany, Ahmad Almogren, Ayman Altameem, Ateeq Ur Rehman

“…Brain tumors are among the most significant and challenging medical conditions because of their sometimes-fatal outcomes and complexity of treatment options. Early, exact detection of brain tumors is essential for both the most effective treatment programs and much higher patient survival rates. …”
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Eeg-based detection of epileptic seizures in patients with disabilities using a novel attention-driven deep learning framework with SHAP interpretability by Tawfeeq Shawly, Ahmed A. Alsheikhy

“…Additionally, the computational complexity of the proposed framework was evaluated in terms of floating-point operations per second (FLOPs) and the total number of parameters, ensuring its efficiency for real-time biomedical applications. …”
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RDW-YOLO: A Deep Learning Framework for Scalable Agricultural Pest Monitoring and Control by Jiaxin Song, Ke Cheng, Fei Chen, Xuecheng Hua

“…Due to target diversity, life-cycle variations, and complex backgrounds, traditional pest detection methods often struggle with accuracy and efficiency. …”
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Enhancing Wheat Spike Counting and Disease Detection Using a Probability Density Attention Mechanism in Deep Learning Models for Precision Agriculture by Ruiheng Li, Wenjie Hong, Ruiming Wu, Yan Wang, Xiaohan Wu, Zhongtian Shi, Yifei Xu, Zixu Han, Chunli Lv

“…Addressing the shortcomings of traditional detection methods, we propose an advanced feature extraction strategy and a model based on the probability density attention mechanism, designed to more effectively handle feature extraction in complex backgrounds and dense areas. …”
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FM‐YOLOv8:Lightweight gesture recognition algorithm by Fanghai Li, Xitai Na, Jinshuo Shi, Qingbin Sun

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A MALDI-TOF MS-based multiple detection panel of drug resistance-associated multiple single-nucleotide polymorphisms in Candida tropicalis by Feifei Wan, Min Zhang, Jian Guo, Huiping Lin, Xiaoguang Zhou, Lixin Wang, Wenjuan Wu

“…Current methods for detecting drug resistance are limited by the long turnaround time of antifungal susceptibility testing, low throughput of Sanger sequence to target resistance mutations, complex data analysis, and high costs of second-generation sequencing. …”
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Determination of Nitrofuran Metabolites in Complex Food Matrices Using a Rough, Cheap, Easy-Made Wooden-Tip-Based Solid-Phase Microextraction Probe and LC-MS/MS by Xiaoming Gong, Kai Li, Wenjuan Xu, Liming Jin, Mengxiao Liu, Mengmeng Hua, Guoning Tian

“…In addition, the main parameters affecting the SPME procedure efficiency were investigated in detail and the optimal conditions were found. …”
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A Comparative Study of Two-Stage Intrusion Detection Using Modern Machine Learning Approaches on the CSE-CIC-IDS2018 Dataset by Isuru Udayangani Hewapathirana

“…The findings emphasize the complementary nature of the two approaches, suggesting that a combined model could achieve a balance between accuracy and computational efficiency. This work provides valuable insights for designing scalable, high-performance intrusion detection systems in modern network environments.…”
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A Novel Training Strategy for Deep Learning Model Compression Applied to Automatic Modulation Classification by Mateus A. Goldbarg, Micael Balza, Sergio N. Silva, Lucileide M. D. Silva, Marcelo A. C. Fernandes

“…However, their computational demands pose a significant hurdle for real-time modulation detection. To tackle this issue, a novel training strategy is proposed in this study. …”
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Cross-attention swin-transformer for detailed segmentation of ancient architectural color patterns by Lv Yongyin, Yu Caixia

“…Traditional approaches, including convolutional neural networks (CNNs) and standard transformer-based models, have achieved significant success; however, they often face challenges in capturing fine-grained details and maintaining efficiency across diverse datasets. These methods struggle with balancing precision and computational efficiency, especially when dealing with complex patterns and high-resolution images.MethodsTo address these limitations, we propose a novel segmentation model that integrates a hierarchical vision transformer backbone with multi-scale self-attention, cascaded attention decoding, and diffusion-based robustness enhancement. …”
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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…This method provides technical support for railroad construction safety monitoring and effectively addresses personnel detection tasks in complex construction environments.…”
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Real-Time Evaluation of the Improved Eagle Strategy Model in the Internet of Things by Venushini Rajendran, R Kanesaraj Ramasamy

“…Web services, facilitated by APIs, offer a modular approach to integrating and streamlining complex business processes. However, real-time monitoring and optimal service selection within large-scale, cloud-based repositories remain significant challenges. …”
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