HDF-Net: Hierarchical Dual-Branch Feature Extraction Fusion Network for Infrared and Visible Image Fusion by Yanghang Zhu, Mingsheng Huang, Yaohua Zhu, Jingyu Jiang, Yong Zhang

“…Remarkably, we propose a pin-wheel-convolutional transformer (PCT) module that integrates local convolutional processing with directional attention to improve low-frequency feature extraction, thereby enabling more robust global–local context modeling. …”
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Antenna Optimization Design Based on Deep Gaussian Process Model by Xin-Yu Zhang, Yu-Bo Tian, Xie Zheng

“…In order to solve this problem, this study constructs a deep GP (DGP) model by using the structural form of convolutional neural network (CNN) and combining it with GP. …”
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InGSA: integrating generalized self-attention in CNN for Alzheimer's disease classification by Faisal Binzagr, Anas W. Abulfaraj

“…Furthermore, several GSA heads are used to exploit other dependency structures of global features as well. Our evaluation of InGSA on a two benchmark dataset, using various pre-trained networks, demonstrates the GSA's superior performance.…”
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Generation driven understanding of localized 3D scenes with 3D diffusion model by Hao Sun, Junping Qin, Zheng Liu, Xinglong Jia, Kai Yan, Lei Wang, Zhiqiang Liu, Shaofei Gong

“…However, the existing diffusion models primarily focus on the global structure and are constrained by predefined dataset categories, which are unable to accurately resolve the detailed structure of complex 3D scenes. …”
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DECTNet: A detail enhanced CNN-Transformer network for single-image deraining by Liping Wang, Guangwei Gao

“…While CNNs are highly effective at extracting local information, they struggle to capture global context. Conversely, Transformers excel at capturing global information but often face challenges in preserving spatial and structural details. …”
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An industrial carbon block instance segmentation algorithm based on improved YOLOv8 by Runjie Shi, Zhengbao Li, Zewei Wu, Wenxin Zhang, Yihang Xu, Gan Luo, Pingchuan Ma, Zheng Zhang

“…YOLOv8-HDSA adds a convolutional self-attention mechanism with residual structure to the head, preserving important local information of carbon blocks and improving the ability to extract fine-grained edge details and global features of carbon blocks. …”
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FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction by Xuekai Zhu, Juan Liu, Jian Zhang, Zhihui Yang, Feng Yang, Xiaolei Zhang

“…Owing to the structural limitations of CNN, features extracted from this method are local patterns that lack global information. …”
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Data-Enabled Intelligence in Complex Industrial Systems Cross-Model Transformer Method for Medical Image Synthesis by Zebin Hu, Hao Liu, Zhendong Li, Zekuan Yu

“…Recently, generative adversarial network (GAN) models are applied to many medical image synthesis tasks and show prior performance, since they enable to capture structural details clearly. However, GAN still builds the main framework based on convolutional neural network (CNN) that exhibits a strong locality bias and spatial invariance through the use of shared weights across all positions. …”
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SwinCNet leveraging Swin Transformer V2 and CNN for precise color correction and detail enhancement in underwater image restoration by Chun Yang, Liwei Shao, Yi Deng, Jiahang Wang, Hexiang Zhai

“…Current methods face difficulties in effectively balancing local detail preservation with global information integration. This study proposes SwinCNet, an innovative deep learning architecture that incorporates an enhanced Swin Transformer V2 following primary convolutional layers to achieve synergistic processing of local details and global dependencies. …”
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GIVTED-Net: GhostNet-Mobile Involution ViT Encoder-Decoder Network for Lightweight Medical Image Segmentation by Resha Dwika Hefni Al-Fahsi, Ahmad Naghim Fauzaini Prawirosoenoto, Hanung Adi Nugroho, Igi Ardiyanto

“…Nevertheless, conventional CNN layers, such as convolution and pooling, demonstrate a spatial inductive bias that constrains their ability to instantly capture global context information. …”
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Semantic ECG hash similarity graph by Yixian Fang, Shilin Zhang, Yuwei Ren

“…However, most existing graph structures primarily focus on local similarity while overlooking global semantic correlation. …”
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DBRSNet: a dual-branch remote sensing image segmentation model based on feature interaction and multi-scale feature fusion by Yong Ji, Wenbin Shi, Jingsheng Lei, Jiayin Ding

“…In DBRSNet, the Feature-Guided Selection Module (FGSM) adaptively integrates complementary features from CNN and Transformer branches, while the Convolutional Attention Integration Module (CAIM) enhances global dependencies and spectral correlations, ensuring a more comprehensive feature representation. …”
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Edge-aware joint neural denoising and normal estimation for mobile and handheld laser point clouds by T. Zhang, S. Filin

“…To extract contextual information it introduces densely packed graph convolution layers and a global attention mechanism. …”
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A High-Precision Defect Detection Approach Based on BiFDRep-YOLOv8n for Small Target Defects in Photovoltaic Modules by Yi Lu, Chunsong Du, Xu Li, Shaowei Liang, Qian Zhang, Zhenghui Zhao

“…With the accelerated transition of the global energy structure towards decarbonization, the share of PV power generation in the power system continues to rise. …”
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Two-Branch Filtering Generative Network Based on Transformer for Image Inpainting by Feihan Cao, Qifeng Zhu, Yasheng Chang, Min Sun

“…This module utilizes predictive filtering constructed from convolutions to leverage local interactions, while simultaneously employing a transformer architecture with kernels from the predictive network to capture global correlations. …”
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DEFIF-Net: A lightweight dual-encoding feature interaction fusion network for medical image segmentation. by Zhanlin Ji, Shengnan Hao, Quanming Zhao, Zidong Yu, Hongjiu Liu, Lei Li, Ivan Ganchev

“…Firstly, in the encoding stage of DEFIF-Net, a global dependency fusion branch is introduced as an additional encoder to capture distant feature dependencies, whereby the neighboring and distant feature dependencies are effectively integrated by the newly designed feature interaction fusion convolution. …”
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A Comprehensive Evaluation of Monocular Depth Estimation Methods in Low-Altitude Forest Environment by Jiwen Jia, Junhua Kang, Lin Chen, Xiang Gao, Borui Zhang, Guijun Yang

“…The evaluated models include both self-supervised and supervised approaches, employing different network structures such as convolutional neural networks (CNNs) and Vision Transformers (ViTs). …”
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Multilevel Feature Gated Fusion Based Spatial and Frequency Domain Attention Network for Joint Classification of Hyperspectral and LiDAR Data by Cuiping Shi, Zhipeng Zhong, Shihang Ding, Yeqi Lei, Liguo Wang, Zhan Jin

“…Hyperspectral images provide rich spectral information, while LiDAR data supplements three-dimensional spatial structural information. The combination of the two can effectively improve the accuracy of land cover classification. …”
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Application of Partial Differential Equation Image Classification Methods to the Aesthetic Evaluation of Images by Feifeng Liu, Weihu Wang

“…The structure of a convolution kernel learned by using parallel network structure achieves better classification performance. …”
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Research on Vehicle Target Detection Method Based on Improved YOLOv8 by Mengchen Zhang, Zhenyou Zhang

“…A Lightweight Shared Convolution Detection Head was designed. By designing a shared convolution layer through group normalization, the detection head of the original model was improved, which can reduce redundant calculations and parameters and enhance the ability of global information fusion between feature maps, thereby achieving the purpose of improving computational efficiency. …”
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