Marine Macro-Plastics Litter Features and Their Relation to the Geographical Settings of the Selected Adriatic Islands, Croatia (2018–2023) by Natalija Špeh, Robert Lončarić

“…This study hypothesized that the natural features of the islands influence ML distribution. …”
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Inventory and distribution feature of shallow landslides triggered by heavy rain event in Shaoguan, Guangdong Province in April 2024 by Yuandong HUANG, Chong XU, Yi LIU, Xiangli HE, Xiaoyi SHAO, Binbin ZHAO, Xiaoang KONG

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MBFE-UNet: A Multi-Branch Feature Extraction UNet with Temporal Cross Attention for Radar Echo Extrapolation by Huantong Geng, Han Zhao, Zhanpeng Shi, Fangli Wu, Liangchao Geng, Kefei Ma

“…In this paper, we propose a UNet-based multi-branch feature extraction model named MBFE-UNet for radar echo extrapolation to mitigate these issues. …”
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Optimizing Fire Scene Analysis: Hybrid Convolutional Neural Network Model Leveraging Multiscale Feature and Attention Mechanisms by Shakhnoza Muksimova, Sabina Umirzakova, Mirjamol Abdullaev, Young-Im Cho

“…The rapid and accurate detection of fire scenes in various environments is crucial for effective disaster management and mitigation. Fire scene classification is a critical aspect of modern fire detection systems that directly affects public safety and property preservation. …”
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A Degradation Warning Method for Ultra-High Voltage Energy Devices Based on Time-Frequency Feature Prediction by Pinzhang Zhao, Lihui Wang, Jian Wei, Yifan Wang, Haifeng Wu

“…Second, we develop an advanced I-Informer prediction network featuring improvements in both the embedding and distillation layers to accurately forecast future changes in DC characteristics. …”
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DCANet: A Dual-Branch Cross-Scale Feature Aggregation Network for Remote Sensing Image Semantic Segmentation by Yanhong Yang, Fei Wang, Haozheng Zhang, Yushan Xue, Guodao Zhang, Shengyong Chen

“…Specifically, to mitigate the information redundancy caused by cross-scale residual learning, we propose a distributed feature aggregation strategy. …”
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MDFusion: Multi-Dimension Semantic–Spatial Feature Fusion for LiDAR–Camera 3D Object Detection by Renzhong Qiao, Hao Yuan, Zhenbo Guan, Wenbo Zhang

“…To mitigate these issues, this paper proposes a novel multi-dimension semantic–spatial feature fusion (MDFusion) method that combines LiDAR and image features in 2D and 3D spaces. …”
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Advancing Artificial Intelligence of Things Security: Integrating Feature Selection and Deep Learning for Real-Time Intrusion Detection by Faisal Albalwy, Muhannad Almohaimeed

“…Specifically, five feature selection methods (correlation-based feature subset selection (CFS), Pearson analysis, gain ratio (GR), information gain (IG) and symmetrical uncertainty (SU)) were integrated with PCA to optimise feature dimensionality and enhance predictive performance. …”
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Multi-Scale Feature Fusion GANomaly with Dilated Neighborhood Attention for Oil and Gas Pipeline Sound Anomaly Detection by Yizhuo Zhang, Zhengfeng Sun, Shen Shi, Huiling Yu

“…Firstly, to mitigate information loss during network deepening, a Multi-scale Feature Fusion module is proposed to merge the encoded and decoded feature maps at different dimensions, enhancing low-level detail and high-level semantic information. …”
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Features of the species composition based on the trophic analysis of artificial woody plantations of the Kryvyi Rih mining and industrial district by Maksym Kvitko, Olena Lykholat, Tetyana Lykholat, Mykhailo Holubiev, Yuriy Lykholat

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Efficient Explainable Models for Alzheimer’s Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning by Yogita Dubey, Aditya Bhongade, Prachi Palsodkar, Punit Fulzele

“…Extensive feature analysis was conducted to identify the most impactful clinical features followed by feature reduction techniques to focus on the most informative clinical features, reducing model complexity and overfitting risks. …”
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An Intelligent Smart Dynamic Feature Analysis Based Approach by Utilizing Deep Learning to Improve the Breast Cancer Detection by Seong-O Shim, Lal Hussain, Eesa Alsolami, Monagi H. Alkinani

“…Moving away from the traditional approaches with inherent pre-processing and feature extraction constraints, this research focuses on a two-pronged improvement strategy: improved mammogram quality and highly optimized deep learning architecture. …”
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Simulation-Based Electrothermal Feature Extraction and FCN–GBM Hybrid Model for Lithium-ion Battery Temperature Prediction by Luyan WANG, Hongliang HAO, Zhongkang ZHOU, Huimin MA, Jin ZHAO, Zeyang LIU, Qiangqiang LIAO

“…Moreover, the use of single input features leads to larger prediction errors. These results confirm the effectiveness of the FCN-enhanced GBM model and the advantage of feature fusion using voltage and resistance, providing practical insights for improving thermal management and risk mitigation in lithium-ion battery systems.…”
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Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

“…Initially, 35 features were identified based on expert opinion and a comprehensive literature review; the integrated results of the feature selection methods reduced the feature set to 14. …”
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Adaptive Cluster-Based Normalization for Robust TOPSIS in Multicriteria Decision-Making by Vitor Anes, António Abreu

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The potential of agroforestry to reduce atmospheric greenhouse gases in Canada: Insight from pairwise comparisons with traditional agriculture, data gaps and future research by Mark Baah-Acheamfour, Scott X. Chang, Edward W. Bork, Cameron N. Carlyle

“…Canadian agriculture is a source of greenhouse gases (GHG) and agroforestry has the potential to sequester carbon (C), and mitigate agricultural GHG emissions. Agroforestry systems are common features in Canada’s agricultural landscape; however, there are limited empirical data to support implementation of agroforestry practices for GHG mitigation. …”
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D3L-SLAM: A Comprehensive Hybrid Simultaneous Location and Mapping System with Deep Keypoint, Deep Depth, Deep Pose, and Line Detection by Hao Qu, Congrui Wang, Yangfan Xu, Lilian Zhang, Xiaoping Hu, Changhao Chen

“…We further enhance perception in low-texture areas by incorporating line features in the front-end and mitigate scale degradation with learned depth estimates. …”
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Infrastructure profile and surrounding land use determine bird-train collision risk in a High-Speed Railway by Lourenço Falcão Rodrigues, Jesús Herranz Barrera, Eladio L. García de la Morena, Cristina Mata Estacio, Juan E. Malo

“…This research offers critical insights into the environmental impacts of HSRs on avian species, offering guidance for future infrastructure development and mitigation strategies.…”
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Fractional amplitude of low-frequency fluctuations during music-evoked autobiographical memories in neurotypical older adults by Teresa Lesiuk, Kaitlyn Dillon, Giulia Ripani, Ioannis Iliadis, Gabriel Perez, Bonnie Levin, Xiaoyan Sun, Roger McIntosh

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Multimodal radiomics model with triple -timepoint contrast-enhanced ultrasound for precise diagnosis of C-TIRADS 4 thyroid nodules by Linlin Shao, Lili Zhang, Lifang Liu, Fangfang Sun, Hongyu Li, Tongfeng Liu, Feng Hu, Lirong Zhao

“…ROIs were manually delineated (3D-Slicer), with radiomics features extracted (PyRadiomics) and selected via mRMR and LASSO. …”
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