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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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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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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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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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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A Neural Network with Multiscale Convolution and Feature Attention Based on an Electronic Nose for Rapid Detection of Common Bunt Disease in Wheat Plants by Zhizhou Ren, Kun Liang, Yihe Liu, Xiaoxiao Wu, Chi Zhang, Xiuming Mei, Yi Zhang

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

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SVEA: an accurate model for structural variation detection using multi-channel image encoding and enhanced AlexNet architecture by Taixing Qiu, Jiawei Li, Yan Guo, Limin Jiang, Jijun Tang

“…Additionally, SVEA integrates multi-head self-attention mechanisms and multi-scale convolution modules, enhancing its ability to capture global context and multi-scale features. …”
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U-Shaped Dual Attention Vision Mamba Network for Satellite Remote Sensing Single-Image Dehazing by Tangyu Sui, Guangfeng Xiang, Feinan Chen, Yang Li, Xiayu Tao, Jiazu Zhou, Jin Hong, Zhenwei Qiu

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Global information aware network with global interaction graph attention for infrared small target detection by Ruimin Yang, Yidan Zhang, Guangshuai Gao, Liang Liao, Chunlei Li

“…However, distinguishing small infrared targets from similar backgrounds is challenging due to their lack of structural and textural characteristics. To address these challenges, this study proposes a novel global information‐aware network with global interaction graph attention (GIGA) for infrared small target detection. …”
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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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D3GNN: Double dual dynamic graph neural network for multisource remote sensing data classification by Teng Yang, Song Xiao, Jiahui Qu

“…Graph Neural Network (GNN), capable of extracting features from the topological structure, is considered as a solution for capturing global information. …”
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A Novel Hierarchical Multimodal Recommender With Enhanced Global Collaborative Signals by Peng Yi, Lu Chen, Zhaoxian Li, Cheng Yang

“…Specifically, modality features are first utilized to identify neighboring relationships, and similar users (items) are steadily merged together to form modality-specific hierarchical structures. Then, with the proper graph convolution operation on each hierarchy, the crucial global collaborative signals can be effectively extracted and integrated into the modality-specific user (item) embeddings. …”
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