Neural Networks for Operational SYM‐H Forecasting Using Attention and SWICS Plasma Features by Armando Collado‐Villaverde, Pablo Muñoz, Consuelo Cid

“…Abstract In this work, we present an Artificial Neural Network for operational forecasting of the SYM‐H geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind plasma features and previous SYM‐H values. …”
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Optimal Features Driven Attention Network With Medium-Scale Benchmark for Wheat Diseases Recognition by Muhammad Islam, Mohammed Aloraini, Shabana Habib, Meshari D. Alanazi, Ishrat Khan, Aqib Khan

“…However, the literature relied on inadequate feature selection acquired from computationally expensive backbones followed by shallow layered networks. …”
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A lightweight YOLO network using temporal features for high-resolution sonar segmentation by Sen Gao, Sen Gao, Wei Guo, Wei Guo, Gaofei Xu, Gaofei Xu, Ben Liu, Ben Liu, Yu Sun, Bo Yuan

“…Current segmentation methods often struggle to balance processing speed with accuracy.MethodsWe propose a novel YOLO-based segmentation framework featuring: (1) A lightweight backbone(ghostnet) network optimized for sonar imagery processing (2) A bypass BiLSTM network for temporal feature learning across consecutive frames. …”
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Anomaly Detection Approach Based on Deep Neural Network and Dropout by Zaid Hussien et al.

“…They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. …”
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Hyperspectral Attention Network for Object Tracking by Shuangjiang Yu, Jianjun Ni, Shuai Fu, Tao Qu

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Intelligent recognition method for urban road grid patterns by fusing mesh and road features by Zhekun Huang, Haizhong Qian, Zhongxiang Cai, Andong Wang, Junwei Wang, Feng Xiong

“…Then, the research focus is refined to the road segment level, where the preliminary results are optimized by extracting the geometric and directional features of the road segments. This method significantly outperformed methods based on single research objects across several evaluation metrics, with a performance improvement ranging from 0.79–44.87%. …”
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Battery Life Evaluation Method Based on Temporal Convolution Network by SUN Yushu, AN Juan, HUANG Cunqiang, ZHANG Shunzhen, DANG Yanyang, PEI Wei, TANG Xisheng

“…ObjectiveTo improve the technical economy of battery system applications, a temporal convolutional network (TCN) is employed to evaluate battery life from two perspectives: State of health (SOH) and remaining useful life (RUL). …”
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SHAP Informed Neural Network by Jarrod Graham, Victor S. Sheng

“…Despite computational challenges, these methods provide a foundation for exploring how feature importance can inform neural network training, presenting promising directions for future research on scalable and efficient optimization techniques.…”
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Evaluating the efficacy of fuzzy Bayesian networks for financial risk assessment by Xiong Tingyan, Liu Zeping, Zhang Minghong

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RaNet: a residual attention network for accurate prostate segmentation in T2-weighted MRI by Muhammad Arshad, Chengliang Wang, Muhammad Wajeeh Us Sima, Jamshed Ali Shaikh, Salem Alkhalaf, Fahad Alturise

“…To address these challenges, we propose RaNet (Residual Attention Network), a novel framework based on ResNet50, incorporating three key modules: the DilatedContextNet (DCNet) encoder, the Multi-Scale Attention Fusion (MSAF), and the Feature Fusion Module (FFM). …”
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SHARP-Net: A Refined Pyramid Network for Deficiency Segmentation in Culverts and Sewer Pipes by Rasha Alshawi, Md Meftahul Ferdaus, Md Tamjidul Hoque, Kendall Niles, Ken Pathak, Steve Sloan

“…SHARP-Net combines multiscale feature fusion, depthwise separable convolutions, and fine-tuned Haar-like features to enhance performance while reducing computational complexity. …”
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CDMRNet: multimodal meta-adaptive reasoning network with dynamic causal modeling and co-evolution of quantum states by Shengwei Wang, Keda Chen, Mengduo Yu, Pengjiao Zhao, Hui Duan

“…Abstract Cross-modal reasoning tasks face persistent challenges such as cross-modal inference of causal dependencies with coarse-grained, weak resistance to noise, and weak interaction of spatial-temporal features. To address these issues, the article proposes a dynamic causal-aware collaborative quantum state evolution multimodal reasoning architecture, Causal-aware Dynamic Multimodal Reasoning Network (CDMRNet). …”
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Dynamic evolution and network structure characteristics of the wellbeing eco-efficiency of cities in the Yellow River Basin, China by Meixia Wang, Qingyun Zheng, Li Liu

“…Clarifying its spatial and temporal dynamic evolution and network structure characteristics is crucial for promoting the ecological protection and high-quality development in the entire Yellow River Basin (YRB). …”
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Trust evaluation based on evidence theory in online social networks by Jian Wang, Kuoyuan Qiao, Zhiyong Zhang

“…Trust is an important criterion for access control in the field of online social networks privacy preservation. In the present methods, the subjectivity and individualization of the trust is ignored and a fixed model is built for all the users. …”
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Evaluation of Bayesian network scoring functions in polychotomous data analysis by Xuejia Ke, Katherine Keenan, V. Anne Smith

“…Among these, the BDe scoring function requires specifying hyperparameters that influence the priors on the network parameters. This study evaluates the performance of four scoring functions—AIC, BIC, BDe, and log-likelihood—particularly with highly polychotomous data. …”
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A Comparative Analysis of Student Performance Prediction: Evaluating Optimized Deep Learning Ensembles Against Semi-Supervised Feature Selection-Based Models by Jose Antonio Lagares Rodríguez, Norberto Díaz-Díaz, Carlos David Barranco González

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Importance Evaluation of Power Grid Transmission Lines Based on Multidimensional Information Feature Mapping by Keji Chen, Yingqi Tie, Maohua Li

“…To address the limitations in existing transmission line evaluation methods, such as reliance on single evaluation metrics, insufficient consideration of information transmission between adjacent lines, and the impact of line failures on system load loss, this paper proposes a comprehensive evaluation method based on multidimensional information feature mapping. …”
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Multilevel Feature Cross-Fusion-Based High-Resolution Remote Sensing Wetland Landscape Classification and Landscape Pattern Evolution Analysis by Sijia Sun, Biao Wang, Zhenghao Jiang, Ziyan Li, Sheng Xu, Chengrong Pan, Jun Qin, Yanlan Wu, Peng Zhang

“…To address these issues, this study proposes the multilevel feature cross-fusion wetland landscape classification network (MFCFNet), which combines the global modeling capability of Swin Transformer with the local detail-capturing ability of convolutional neural networks (CNNs), facilitating discerning intraclass consistency and interclass differences. …”
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3D Point Cloud Fusion Method Based on EMD Auto-Evolution and Local Parametric Network by Wen Chen, Hao Chen, Shuting Yang

“…In the first stage, EMD is introduced as a key metric for evaluating the fusion results, and a point cloud fusion method based on EMD auto-evolution is constructed. …”
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Demand response potential evaluation based on feature fusion with expert knowledge and multi‐image by Jiale Liu, Xinlei Cai, Zijie Meng, Xin Jin, Zhangying Cheng, Tingzhe Pan

“…Additionally, the typical load profile's recurrence plot, Markov leapfrog field, and Gramian angle field are created and incorporated into the colourful image as inputs. Then, the evaluation results are obtained by a two‐stream neural network fusing multivariate features. …”
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