HEE-SegGAN: A holistically-nested edge enhanced GAN for pulmonary nodule segmentation. by Yong Wang, Seri Mastura Mustaza, Mohammad Syuhaimi Ab-Rahman, Siti Salasiah Mokri

“…The generator adopted the HED-U-Net, while the discriminator was implemented as a convolutional neural network. Two inverted residual modules were embedded within the HED-U-Net to fuse inter-slice spatial information and enhance salient features using a channel attention mechanism. …”
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Fault diagnosis method of mine hoist main bearing with small sample based on VAE-WGAN by Fan JIANG, Hongyan SONG, Xi SHEN, Zhencai ZHU, Shuman CHENG

“…By integrating cross channel and spatial information, more attention is paid to fault features. …”
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Recognition Algorithm of AE Signal of Rock Fracture Based on Multiscale 1DCNN-BLSTM by Weihua Wang

“…In response to the interference characteristics of acoustic emission signal data, a multiscale one-dimensional convolutional neural network embedded with efficient channel attention (ECA) module was incorporated into the model, and multiscale convolutional kernels were used to extract features of different levels of precision. …”
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Dynamic graph attention network based on multi-scale frequency domain features for motion imagery decoding in hemiplegic patients by Yinan Wang, Yinan Wang, Lizhou Gong, Yang Zhao, Yewei Yu, Hanxu Liu, Xiao Yang

“…Additionally, MFF-DANet integrates a graph attention convolutional network to capture spatial topological features across different electrode channels, utilizing electrode positions as prior knowledge to construct and update the graph adjacency matrix. …”
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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…In this study, within each procedure, samples are represented in a two-dimensional (feature-time) form, and procedures are constructed as channels to build three-dimensional (feature-time-procedure) samples. …”
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DiffMamba: semantic diffusion guided feature modeling network for semantic segmentation of remote sensing images by Zhen Wang, Nan Xu, Zhuhong You, Shanwen Zhang

“…MVTrans can observe the spatial location information of the object region from various perspectives to obtain refined global context details. …”
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Multi-Neighborhood Sparse Feature Selection for Semantic Segmentation of LiDAR Point Clouds by Rui Zhang, Guanlong Huang, Fengpu Bao, Xin Guo

“…To address these problems, a sparse feature dynamic graph convolutional neural network, abbreviated as SFDGNet, is constructed in this paper for LiDAR point clouds of complex scenes. …”
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WTDBNet: A Wavelet Transform-Based Dual-Stream Backbone Network for Fine-Grained Ship Detection by Wei Cao, Xinyu Zhao, Hongqi Wang, Yuxin Hu

“…These components are fused via channel and spatial attention mechanisms, thereby improving the model’s ability to extract discriminative features. …”
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Multi-scale feature pyramid network with bidirectional attention for efficient mural image classification. by Shulan Wang, Siyu Liu, Mengting Jin, Pingmei Fan

“…Second, a bidirectional LSTM-driven attention module iteratively optimizes channel and spatial weights, enhancing detail perception for low-frequency categories. …”
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A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding by Juntao Xue, Feiyue Ren, Xinlin Sun, Miaomiao Yin, Jialing Wu, Chao Ma, Zhongke Gao

“…The structure of the multifrequency brain network matches the activity profile of the brain properly, which combines the information of channel and multifrequency. The filter bank common spatial pattern (FBCSP) algorithm filters the MI-based EEG signals in the spatial domain to extract features. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Attention weights are then generated to simultaneously fuse spatial and channel information, significantly improving the model's accuracy in identifying crack regions in levees, particularly under complex lighting and background interference. …”
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CSI-based symmetric encryption end-to-end communication system by Yongli AN, Zongrui LI, Haifei BAI, Xueyu MI

“…To address the issue of information leakage caused by key theft during transmission, a symmetric encryption end-to-end communication system based on channel state information (CSI) was proposed. The proposed system employed convolutional neural networks to construct the transmitter, receiver, and key generator, optimizing the encoding and decoding process in an end-to-end manner. …”
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3D animation design image detail enhancement based on intelligent fuzzy algorithm by Pu Haitao, Pu Yuang

“…The image was divided into superpixel regions using SLIC (Simple Linear Iterative Clustering) algorithm, and local features such as texture, contrast, and edge intensity were extracted; in the SRGAN model, the generator improved image resolution through deep residual blocks and Convolutional Neural Network (CNN), while the discriminator optimized the generated image quality through adversarial training; at the same time, a Fuzzy Logic System (FLS) was constructed to dynamically adjust the image fuzzy degree; channel and spatial attention modules in the generator were integrated to enhance key area details. …”
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YOLO-MARS: An Enhanced YOLOv8n for Small Object Detection in UAV Aerial Imagery by Guofeng Zhang, Yanfei Peng, Jincheng Li

“…Finally, a dynamic WIoU evaluation function is implemented, constructing adaptive penalty terms based on the spatial distribution characteristics of predicted and ground-truth bounding boxes, thereby optimizing the boundary localization accuracy of densely packed small targets from the UAV viewpoint. …”
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TFF-Net: A Feature Fusion Graph Neural Network-Based Vehicle Type Recognition Approach for Low-Light Conditions by Huizhi Xu, Wenting Tan, Yamei Li, Yue Tian

“…The model employs multi-scale convolutional operations combined with an Efficient Channel Attention (ECA) module to extract discriminative local features, while independent convolutional layers capture hierarchical global representations. …”
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A dual-branch deep learning model based on fNIRS for assessing 3D visual fatigue by Yan Wu, Yan Wu, Yan Wu, TianQi Mu, SongNan Qu, XiuJun Li, XiuJun Li, XiuJun Li, Qi Li, Qi Li, Qi Li

“…Given the time-series nature of fNIRS data and the variability of fatigue responses across different brain regions, a dual-branch convolutional network was constructed to separately extract temporal and spatial features. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…Specifically, based on the YOLOv5 framework, a dual strategy for the lightweight network is adopted as follows: On the one hand, to address the limited nonlinear representation ability of the original network, a global channel attention mechanism is embedded and a feature extraction module, GCCR-GhostNet, is constructed, which can effectively enhance the network’s feature extraction capability and high-frequency noise suppression, while reducing computational cost. …”
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NRGS-Net: A Lightweight Uformer with Gated Positional and Local Context Attention for Nighttime Road Glare Suppression by Ruoyu Yang, Huaixin Chen, Sijie Luo, Zhixi Wang

“…Furthermore, we introduced an improved Uformer backbone named LCAtransformer, in which the downsampling layers adopt efficient depthwise separable convolutions to reduce computational cost while preserving critical spatial information. …”
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YOLOv10-CBRC: A high-precision document image layout analysis model by Zhenjie Wu, Weilan Wang, Hongrui Li

“…Building upon YOLOv10 as the baseline model, the proposed model implements three key improvements: (1) the replacement of the Partial Self-Attention (PSA) module with the Convolutional Block Attention Module (CBAM), which enhances perception of channel-wise information and spatial localization of objects,(2) the adoption of dual-branch Re-upsample and Re-SCDown modules (2Re), which facilitates more effective utilization of multi-scale information,(3) the design of a novel classification feature processor, CIBwithResidualCV3 (CRCV3), which improves performance in classification tasks.Experimental results demonstrate that YOLOv10-CBRC achieves a mAP $$_{50\text {-}95}$$ 50 - 95 of 77.6% on the AbaTND, while YOLOv10-RC reaches mAP $$_{50\text {-}95}$$ 50 - 95 scores of 70.6% and 74.6% on the $$D^4LA$$ D 4 L A and IIIT-AR-13K datasets, respectively, significantly outperforming baseline model. …”
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Time-Series Forecasting Method Based on Hierarchical Spatio-Temporal Attention Mechanism by Zhiguo Xiao, Junli Liu, Xinyao Cao, Ke Wang, Dongni Li, Qian Liu

“…A hierarchical feature fusion architecture is constructed to achieve multi-dimensional alignment of local spatial and global temporal features. …”
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