User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…Furthermore, our findings underscore significant improvements in FL training efficiency, paving the way for advanced applications such as autonomous driving and augmented reality in 5G and next-generation O-RAN networks.…”
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An Optimization Method for PCB Surface Defect Detection Model Based on Measurement of Defect Characteristics and Backbone Network Feature Information by Huixiang Liu, Xin Zhao, Qiong Liu, Wenbai Chen

“…We apply feature map separation-based SPDConv for downsampling, providing PAN-FPN with rich, fine-grained shallow-layer features. Additionally, SLFFM employs the bi-level routing attention (BRA) mechanism as a feature aggregation module, mitigating defect-background similarity issues. …”
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A graph convolutional network approach for hyperspectral image analysis of blueberries physiological traits under drought stress by Md. Hasibur Rahman, Savannah Busby, Sajid Hanif, Md Mesbahul Maruf, Faraz Ahmad, Sushan Ru, Alvaro Sanz-Saez, Jingyi Zheng, Tanzeel U. Rehman

“…The Plant-GCN model utilizes graph convolutional layers that aggregate information from neighboring nodes, effectively capturing complex interactions in the spectral signature and enhancing the prediction of physiological traits. …”
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DMF-YOLO: Dynamic Multi-Scale Feature Fusion Network-Driven Small Target Detection in UAV Aerial Images by Xiaojia Yan, Shiyan Sun, Huimin Zhu, Qingping Hu, Wenjian Ying, Yinglei Li

“…Second, we construct a Multi-scale Feature Aggregation Module (MFAM) that integrates dual-branch spatial attention mechanisms to achieve efficient cross-layer feature fusion, mitigating information conflicts between shallow details and deep semantics. …”
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Low-carbon operation strategy of AC/DC hybrid distribution network considering demand response and distributed robust game by XIAO Wenqiao, LIU Jichun

“…The AC/DC hybrid distribution network has been widely studied due to its advantages such as flexible controllability and DC source-load friendly access, moreover, the increase of demand-side flexible resources makes the efficient utilization of demand response more diverse. …”
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Combining convolutional neural network with transformer to improve YOLOv7 for gas plume detection and segmentation in multibeam water column images by Wenguang Chen, Xiao Wang, Junjie Chen, Jialong Sun, Guozhen Zha

“…First, we sequentially reduce the ELAN (Efficient Layer Aggregation Networks) structure in the backbone network and verify that using the enhanced feature extraction module only in the deep network is more effective in recognising the gas plume targets. …”
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Research on multi dimensional feature extraction and recognition of industrial and mining solid waste images based on mask R-CNN and graph convolutional networks by Shuqin Wang, Na Cheng, Yan Hu

“…The graph structure was input into GCN for high-order feature extraction, where the neighbor information of nodes was aggregated through multi-layer graph convolution to update node features, ultimately fusing the high-order features and primary features output by GCN to obtain multidimensional features for classification, detection, and segmentation tasks, thereby improving the accuracy and efficiency of image analysis. …”
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Aircraft Sensor Fault Diagnosis Based on GraphSage and Attention Mechanism by Zhongzhi Li, Jinyi Ma, Rong Fan, Yunmei Zhao, Jianliang Ai, Yiqun Dong

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Improving Artistic Design With KFDeformNet: Single-Frame Three-Dimensional Cartoon Face Recovery by Tong Sun, Xiaohui Wang, Yichen Qi

“…We evaluate KFDeformNet on various cartoon face datasets, demonstrating that MAKEstimator outperforms state-of-the-art methods in keypoint precision and FRDeformer achieves better 3D recovery with reduced MSE and faster convergence, aided by the Unified Layer Hyper-Network (ULHN) structure. Our results show that KFDeformNet surpasses existing methods in both accuracy and efficiency, enabling improved 3D cartoon face recovery for creative applications.…”
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Towards precision diagnosis: a novel hybrid DC-CAD model for lung disease detection leveraging multi-scale capsule networks and temporal dynamics by Esther Stacy E. B. Aggrey, Qin Zhen, Seth Larweh Kodjiku, Linda Delali Fiasam, Collins Sey, Chiagoziem C. Ukwuoma, Evans Aidoo, Emmanuel Osei-Mensah

“…The model consists of three main contributions: (1) Dilated Capsule Networks for improved multi-scale context aggregation, which captures subtle textural variations, (2) a Channel-wise Attention Mechanism to focus on the most relevant regions of interest, minimizing the impact of irrelevant features, and (3) Distanced LSTM layers to model temporal dependencies across sequential CT scans, providing insights into disease progression. …”
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A Novel Lightweight Framework for Non-Contact Broiler Face Identification in Intensive Farming by Bin Gao, Yongmin Guo, Pengshen Zheng, Kaisi Yang, Changxi Chen

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Revealing soil hydraulic parameters via X–ray tomography depends on the relationship between soil pore structure and saturated hydraulic conductivity by Jiamin Ge, Dongli She, Xinni Ju, Taohong Cao, Yongqiu Xia

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Hierarchical Multiparty Digital Signature for Distributed Systems: Application in Intelligent Vehicle Surveillance by Samir Guediri, Messaoud Abbas, Mostefa Kara, Muath AlShaikh

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YOLO-LSD: A Lightweight Object Detection Model for Small Targets at Long Distances to Secure Pedestrian Safety by Ming-An Chung, Sung-Yun Chai, Ming-Chun Hsieh, Chia-Wei Lin, Kai-Xiang Chen, Shang-Jui Huang, Jun-Hao Zhang

“…The proposed model integrates the C3C2 and the new Efficient Layer Aggregation Network - Convolutional Block Attention Module(ELAN-CBAM) modules to improve the efficiency of feature extraction while reducing computational overhead. …”
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Identifying the Missing Tags in Categorized RFID Systems by Jumin Zhao, Wenting Li, Deng-ao Li

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Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR by Maoyuan Zhang, Xiaojuan Wei, Guojun Liu, Mengxu Chen, Chunxia Zhao, Yingxiao Liu, Zhikang Bao, Yunfeng Guo, Run An, Pengcheng Zhao

“…Second, the RepC3 structure within the cross-scale fusion module is replaced with a module based on the generalized-efficient layer aggregation network that uses a more efficient layer aggregation strategy to improve feature localization. …”
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Research on herd sheep facial recognition based on multi-dimensional feature information fusion technology in complex environment by Fu Zhang, Fu Zhang, Xiaopeng Zhao, Shunqing Wang, Yubo Qiu, Sanling Fu, Yakun Zhang

“…Intelligent management of large-scale farms necessitates efficient monitoring of individual livestock. To address this need, a three-phase intelligent monitoring system based on deep learning was designed, integrating a multi-part detection network for flock inventory counting, a facial classification model for facial identity recognition, and a facial expression analysis network for health assessment. …”
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Ocean Internal Wave Detection in SAR Images Based on Improved YOLOv7 by Limei Cai, Guozhen Zha, Mingsen Lin, Xiao Wang, Honghua Zhang

“…First, in this paper, dynamic snake convolution (DSConv) is introduced into the efficient layer aggregation network (ELAN) module of the backbone network, so that the network can adaptively focus on the irregular strip-like morphology of the ocean internal waves. …”
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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…Furthermore, the DRBNCSPELAN (Dilated Reparam Block with Cross-Stage Partial and Efficient Layer Aggregation Networks) module is introduced to ensure efficient information flow, and a lightweight shared convolution (LSC) detection head is developed. …”
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HP-YOLO: A Lightweight Real-Time Human Pose Estimation Method by Haiyan Tu, Zhengkun Qiu, Kang Yang, Xiaoyue Tan, Xiujuan Zheng

“…Additionally, the Reparameterized Network with Cross-Stage Partial Connections and Efficient Layer Aggregation Network (RepNCSPELAN4) module was incorporated into the detection head, boosting accuracy in detecting small-sized targets through multi-scale convolution and reparameterization techniques while accelerating inference speed. …”
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