ARO-GNN: Adaptive relation-optimized graph neural networks by Yong Lu, Zhengguo Lin

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Complex Network Analytics for Structural–Functional Decoding of Neural Networks by Jiarui Zhang, Dongxiao Zhang, Hu Lou, Yueer Li, Taijiao Du, Yinjun Gao

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Image Inpainting Algorithm Based on Structure-Guided Generative Adversarial Network by Li Zhao, Tongyang Zhu, Chuang Wang, Feng Tian, Hongge Yao

“…The proposed methodology advances a two-stage restoration paradigm: (1) Structural Prior Extraction, where adaptive edge detection algorithms identify residual contours in corrupted regions, and a transformer-enhanced network reconstructs globally consistent structural maps through contextual feature propagation; (2) Structure-Constrained Texture Synthesis, wherein a multi-scale generator with hybrid dilated convolutions and channel attention mechanisms iteratively refines high-fidelity textures under explicit structural guidance. …”
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Fuzzy Optimized Attention Network with Multi-Instance Deep Learning (FOAN-MIDL) for Alzheimer’s Disease Diagnosis with Structural Magnetic Resonance Imaging (sMRI) by Afnan M. Alhassan, Nouf I. Altmami

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MixRformer: Dual-Branch Network for Underwater Image Enhancement in Wavelet Domain by Jie Li, Lei Zhao, Heng Li, Xiaojun Xue, Hui Liu

“…To address the problems of insufficient global modeling in existing CNN models, weak local feature extraction of Transformer and high computational complexity, multi-resolution feature decomposition is performed through a discrete wavelet transform (IWT/DWT) in which low-frequency components retain structure and texture, and high-frequency components capture detail features. …”
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Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques by V. R. Bondarev, K. O. Ivanko, N. G. Ivanushkina

“…A pre-processed and augmented dataset is used for training of the convolutional neural network having an architecture with hierarchical structure and residual block usage. …”
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PoseAlign network for hybrid structure in 2D human pose estimation by Jin Zhang, Yabo Yin, Wenzhong Yang, Doudou Ren, Danny Chen

“…We introduce a novel 2D HPE method called the PoseAlign Network for Hybrid Structure (PAN-HS). PAN-HS leverages the conceptually simple yet effective depth-wise convolution to design two feature extraction blocks: the Spatial Align Block and the Channel Align Block. …”
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Infant cry classification using an efficient graph structure and attention-based model by Qiao X., Jiao S., Li H.

“…Additionally, in order to better classify the efficient graph structure, a local-to-global convolutional neural network (AlgNet) based on convolutional neural networks and attention mechanisms is proposed. …”
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SAR ship target detection method based on CNN structure with wavelet and attention mechanism. by Shiqi Huang, Xuewen Pu, Xinke Zhan, Yucheng Zhang, Ziqi Dong, Jianshe Huang

“…The new method uses the U-Net structure to construct the network, which not only effectively reduces the depth of the network structure, but also significantly improves the complexity of the network. …”
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Structural Similarity-Guided Siamese U-Net Model for Detecting Changes in Snow Water Equivalent by Karim Malik, Colin Robertson

“…A Siamese UNet (Si-UNet) was developed by modifying the model’s last layer to incorporate the structural similarity (SSIM) index. The similarity values from the SSIM index are passed to a contrastive loss function, where the optimization process maximizes SSIM index values for pairs of similar SWE images and minimizes the values for pairs of dissimilar SWE images. …”
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Damage Identification of Conduit Rack in Offshore Platform Structures Based on a Novel Composite Neural Network by Jiaqiang Yan, Yuanchao Qiu, Renhe Shao, Ziqiao Ling, Ruixiang Zhang

“…First, the temporal convolutional network (TCN) breaks through the localisation of traditional convolutional neural networks in modelling the temporal dimension by efficiently extracting the long-term time since of the structural vibration response through an expansive causal convolution mechanism. …”
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A Segmentation Network with Two Distinct Attention Modules for the Segmentation of Multiple Renal Structures in Ultrasound Images by Youhe Zuo, Jing Li, Jing Tian

“…Furthermore, the triple-branch multi-head self-attention mechanism leverages the different convolution layers to obtain diverse receptive fields, capture global contextual information, compensate for the local receptive field limitations of convolution operations, and boost the segmentation performance. …”
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Removing Stripe Noise From Infrared Cloud Images via Deep Convolutional Networks by Pengfei Xiao, Yecai Guo, Peixian Zhuang

“…To further improve the performance, we propose a local-global combination structure model, which combines the representations of different layers for recovering the rich details of infrared cloud images. …”
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A Deep Learning Inversion Method for 3D Temperature Structures in the South China Sea with Physical Constraints by Dongcan Xu, Yahao Liu, Yuan Kong

“…This study develops a Convolutional Long Short-Term Memory (ConvLSTM) neural network, integrating multi-source satellite remote sensing data, to reconstruct the Ocean Subsurface Temperature Structure (OSTS). …”
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Multi-Source Data-Driven Local-Global Dynamic Multi-Graph Convolutional Network for Bike-Sharing Demands Prediction by Juan Chen, Rui Huang

“…The model utilizes a local-global structure to capture spatial dependencies among individual bike-sharing stations and all stations collectively. …”
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GP-GCN: Global features of orthogonal projection and local dependency fused graph convolutional networks for aspect-level sentiment classification by Subo Wei, Guangli Zhu, Zhengyan Sun, Xiaoqing Li, TienHsiung Weng

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Interesting Concept Mining With Concept Lattice Convolutional Networks by Mohamed Hamza Ibrahim, Rokia Missaoui, Pedro Henrique B. Ruas

“…In this paper, we introduce the Concept Lattice Convolutional Network (<inline-formula> <tex-math notation="LaTeX">$\mathcal {LCN}$ </tex-math></inline-formula>), an efficient semi-supervised learning approach to identify actionable concepts (i.e., interesting conceptual structures) based on a scalable convolutional neural network architecture that operates on concept lattices. …”
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On the convolutive development of elastic substrate media as nano foundation by D. Indronil, IM Nazmul

“…The validity of the proposed model is verified through comparisons with established theories, demonstrating its precision and broader applicability to complex structural scenarios. The convolution-based formulation also enhances the analysis of advanced loading conditions and nonlinear material responses, making it highly adaptable to real-world engineering applications. …”
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Target Tracking via Particle Filter and Convolutional Network by Hongxia Chu, Kejun Wang, Xianglei Xing

“…The global representation is generated by combining local features without changing their structures and space arrangements. …”
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DualPlaqueNet with dual-branch structure and attention mechanism for carotid plaque semantic segmentation and size prediction by Lili Deng, Xingyu Duan, Yongxiang Sun, Yunling Wang, Dongmei Song, Xiaokai Duan

“…Notably, a multi-layer one-dimensional convolutional structure is introduced within the Efficient Channel Attention (ECA) module. …”
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