GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The proposed GAT model showcases its effectiveness and promises results for addressing the OPF problem in the distribution network, as evidenced by performance evaluation metrics.…”
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A Comparative Analysis of Artificial Intelligence Techniques for Single Open-Circuit Fault Detection in a Packed E-Cell Inverter by Bushra Masri, Hiba Al Sheikh, Nabil Karami, Hadi Y. Kanaan, Nazih Moubayed

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Diagnosis of array antennas based on near-field data using Faster R-CNN by Boguang Yang, Yulun Wei, Jixiang Shi, Tao Hong, Liangyu Li, Kai-Da Xu

“…Four different excitation states are trained using the same neural network to compare the effects of excitation faults on feature extraction and classification accuracy. …”
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Perceptual Quality Assessment for Pansharpened Images Based on Deep Feature Similarity Measure by Zhenhua Zhang, Shenfu Zhang, Xiangchao Meng, Liang Chen, Feng Shao

“…Therefore, this paper proposes a perceptual quality assessment method based on deep feature similarity measure. The proposed network includes spatial/spectral feature extraction and similarity measure (FESM) branch and overall evaluation network. …”
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Evaluation of large‐scale cycling environment by using the trajectory data of dockless shared bicycles: A data‐driven approach by Ying Ni, Shihan Wang, Jiaqi Chen, Bufan Feng, Rongjie Yu, Yilin Cai

“…Assessing these environments is crucial, but existing methods face data challenges for large urban networks. This study proposes a data‐driven framework using dockless shared bicycle data to efficiently evaluate large‐scale cycling environments. …”
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Comparative Analysis of Hybrid Attention and Progressive Layering Through a Comprehensive Evaluation of ARU-Net and PLU-Net in Brain Tumour Segmentation by Noman Ahmed Siddiqui, Muhammad Tahir Qadri, Muhammad Ovais Akhter, Tahira Anwar, Fahad Farooq

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Underwater image enhancement using hybrid transformers and evolutionary particle swarm optimization by Ajay Kumar, Gagandeep Berar, Manmohan Sharma, Sakshi, Ajit Noonia, Gunjan Verma

“…The HTN-PSO framework combines the strengths of convolutional neural networks and transformer models to effectively capture low-level features and model long-range dependencies. …”
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Edge-YOLO: Lightweight Multi-Scale Feature Extraction for Industrial Surface Inspection by Wang Guiqiang, Chen Junbao, Li Chengzhang, Lu Shuo

“…The Edge-backbone systematically strengthens edge feature extraction and retention through three synergistic components: an Edge-Sensitive (EdgeS) module for optimized feature initialization, a Cross-Stage-Partial Edge Enhancement (C3E2) module that integrates edge information across network stages, and a Multi-Scale Dilated Convolution (MSDC) module that efficiently fuses multi-scale features through weight-sharing. …”
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Research on multi class pests identification and detection based on fusion attention mechanism with Mask-RCNN-CBAM by Xingwang Wang, Xingwang Wang, Xingwang Wang, Can Hu, Xufeng Wang, Hainie Zha, Xueyong Chen, Shanshan Yuan, Jing Zhang, Jianfeng Liao, Zhangying Ye

“…The framework combines three innovations: (1) a CBAM attention mechanism to amplify pest features while suppressing background noise; (2) a feature-enhanced pyramid network (FPN) for multi-scale feature fusion, enhancing small pest recognition; and (3) a dual-channel downsampling module to minimize detail loss during feature propagation. …”
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Improving unsupervised pedestrian re‐identification with enhanced feature representation and robust clustering by Jiang Luo, Lingjun Liu

“…The network makes the feature at the single‐part level also contain partial information of other body parts, making it more discriminative. …”
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Domain Alignment Dynamic Spectral and Spatial Feature Fusion for Hyperspectral Change Detection by Xuexiang Qin, Yuxiang Zhang, Yanni Dong

“…First, DADSSFF uses the main network to optimize the alignment of the mean (first-order statistics) and correlation (variance, second-order statistics) of the bitemporal images, coordinating features across both levels to alleviate the issue of inconsistent feature distribution. …”
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Multimodal Fake News Detection Incorporating External Knowledge and User Interaction Feature by Lifang Fu, Shuai Liu

“…On the other hand, inspired by the “similarity effect” in social psychology, this paper constructs a user interaction network and defines the weighted GCN by calculating the feature similarity among users to analyze the mutual influence of users. …”
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Multi-Dimensional Feature Fusion and Enhanced Attention Streaming Movie Prediction Algorithm by Hanqing Hu, Tianmu Tian, Chengjing Liu, Xueyuan Bai

“…These features were combined with a long- and short-term memory network to explore their internal correlations. …”
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Multispectral Target Detection Based on Deep Feature Fusion of Visible and Infrared Modalities by Yongsheng Zhao, Yuxing Gao, Xu Yang, Luyang Yang

“…Firstly, the YOLOv5 architecture is redesigned into a two-stream backbone network, incorporating a midway fusion strategy to integrate multimodal features from the C3 to C5 layers, thereby enhancing detection accuracy and robustness. …”
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A novel recommender system using light graph convolutional network and personalized knowledge-aware attention sub-network by Rasoul Hassanzadeh, Vahid Majidnezhad, Bahman Arasteh

“…Abstract Recently, graph neural networks (GNNs) have gained prominence in recommender systems (RS) due to their capability to extract vital features and understand intricate relationships. …”
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Algorithm for Recognition of Small Air Targets by Trajectory Features in Passive Bistatic Radar by Dao Van Luc, A. A. Konovalov, Le Minh Hoang

“…Development of an algorithm for recognizing small air targets by trajectory features based on machine learning. Implementation and evaluation of the quality of decision-making methods in a given recognition problem.   …”
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An efficient parallel runoff forecasting model for capturing global and local feature information by Yang-hao Hong, Dong-mei Xu, Wen-chuan Wang, Hong-fei Zang, Xiao-xue Hu, Yan-wei Zhao

“…Additionally, due to the opacity in feature distribution processes of AI models, SHAP (Shapley Additive exPlanations) analysis was used to evaluate the contribution of each feature variable to long-term runoff trends. …”
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WinMRSI: Feature Matching With Window Attention for Multimodal Remote Sensing Image by Yide Di, Yun Liao, Yunan Liu, Hao Zhou, Kaijun Zhu, Mingyu Lu, Qing Duan, Junhui Liu

“…In addition, a dual-branch network is designed to capture contextual dependencies while refining local feature representations. …”
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Feature Constraints Map Generation Models Integrating Generative Adversarial and Diffusion Denoising by Chenxing Sun, Xixi Fan, Xiechun Lu, Laner Zhou, Junli Zhao, Yuxuan Dong, Zhanlong Chen

“…Furthermore, we propose a hybrid attention mechanism that strategically combines channel-wise feature recalibration with coordinate-aware spatial modulation, enabling the enhanced discrimination of geographic features under challenging conditions involving edge ambiguity and environmental noise. …”
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DMFFNet: Dual-Mode Multiscale Feature Fusion-Based Pedestrian Detection Method by Ruizhe Hu, Ting Rui, Yan Ouyang, Jinkang Wang, Qunyan Jiang, Yinan Du

“…To address this problem, we propose a dual-modal multi-scale feature fusion network (DMFFNet). First, we use the MobileNet v3 backbone network to extract the features of dual-modal images as input for the multi-scale fusion attention (MFA) module, combining the idea of multi-scale feature fusion and attention mechanism. …”
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