A novel neuroimaging based early detection framework for alzheimer disease using deep learning by Areej Alasiry, Khlood Shinan, Abeer Abdullah Alsadhan, Hanan E. Alhazmi, Fatmah Alanazi, M. Usman Ashraf, Taseer Muhammad

“…Comparative analyses further validate the superiority of NEDA-DL over existing methods. By integrating structural and functional neuroimaging insights, this approach enhances diagnostic precision and supports clinical decision-making in Alzheimer’s disease detection.…”
Get full text

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. …”
Get full text

Diagnosis of contamination discharge state of porcelain insulators based on GA-CNN by Kegeng Zhang, Jinyuan Liu, Junshuai Zhong, Yizhou Jing

Get full text

Multi-granularity representation learning with vision Mamba for infrared small target detection by Yongji Li, Luping Wang, Shichao Chen

“…Heterogeneous environments and low Signal-to-Clutter Ratio (SCR) pose a challenge for Infrared Small Target Detection (IRSTD). Convolutional Neural Network (CNN) is constrained by the global view. …”
Get full text

Enhanced ResNet50 for Diabetic Retinopathy Classification: External Attention and Modified Residual Branch by Menglong Feng, Yixuan Cai, Shen Yan

“…In this study, we propose an improved ResNet50 model, which replaces the 3 × 3 convolution in the residual structure by introducing an external attention mechanism, which improves the model’s awareness of global information and allows the model to grasp the characteristics of the input data more thoroughly. …”
Get full text

Triangular Mesh Surface Subdivision Based on Graph Neural Network by Guojun Chen, Rongji Wang

“…The tensor voting strategy was used to replace the half-flap spatial transformation method of neural subdivision to ensure the translation, rotation, and scaling invariance of the algorithm. Dynamic graph convolution was introduced to learn the global features of the mesh in the way of stacking, so as to improve the subdivision effect of the network on the extreme input mesh. …”
Get full text

MRP-YOLO: An Improved YOLOv8 Algorithm for Steel Surface Defects by Shuxian Zhu, Yajie Zhou

“…It is further proposed that the RepHead detection head approximates the multi-branch structure of the original training by a single convolution operation. …”
Get full text

Fusion of syntactic enhancement and semantic enhancement for aspect-based sentiment analysis by LIU Yao, WU Yunfei, ZHOU Hongjing, HUANG Shaonian, ZHANG Zhen

“…The graph neural networks mainly focus on the syntactic structure when they are used to model the syntactic dependency tree of a sentence for aspect-based sentiment analysis (ABSA). …”
Get full text

Fusion of syntactic enhancement and semantic enhancement for aspect-based sentiment analysis by LIU Yao, WU Yunfei, ZHOU Hongjing, HUANG Shaonian, ZHANG Zhen

“…The graph neural networks mainly focus on the syntactic structure when they are used to model the syntactic dependency tree of a sentence for aspect-based sentiment analysis (ABSA). …”
Get full text

EEG-based schizophrenia diagnosis using deep learning with multi-scale and adaptive feature selection by Alanoud Al Mazroa, Majdy M. Eltahir, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K, Jaehyuk Cho

“…With the help of atrous convolutions, local and global dependencies within the EEGs can be effectively modeled in this way. …”
Get full text

Dynamic Graph Attention Network for Skeleton-Based Action Recognition by Zhenhua Li, Fanjia Li, Gang Hua

“…To address these challenges, we propose a Dynamic Graph Attention Network (DGAN) that dynamically integrates local structural features and global spatiotemporal dependencies. …”
Get full text

Anterior Cruciate Ligament (ACL) Tear Detection Using Hybrid CNN Transformer by Suthir Sriram, Deependra K. Singh, D. V. Sairam, Nivethitha Vijayaraj, Thangavel Murugan

“…Firstly, MambaConvT utilizes multi-core convolutional networks to achieve higher extraction capability of the ACL tear specific local features from structural MR (Magnetic Resonance) images. …”
Get full text

Vision Transformers (ViTs) for Feature Extraction and Classification of AI-Generated Visual Designs by Qing Yun

Get full text

A Synergistic CNN-DF Method for Landslide Susceptibility Assessment by Jiangang Lu, Yi He, Lifeng Zhang, Qing Zhang, Jiapeng Tang, Tianbao Huo, Yunhao Zhang

“…The complex structures and intricate hyperparameters of existing deep learning (DL) models make achieving higher accuracy in landslide susceptibility assessment (LSA) time-consuming and labor-intensive. …”
Get full text

Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…LTCA efficiently exploited attention mechanisms to extract key features from multi-dimensional flight parameter data samples through adaptive global average pooling (GAP) and one-dimensional convolution, considering global and local information. …”
Get full text

Coseismic Landslide Mapping Based on Trans-UNet and Transfer Learning by Tianhe Ren, Wenping Gong, Jun Chen, Liang Gao, Jiahao Wu, Xuyang Xiang

“…The Trans-UNet model integrates a UNet-like encoder–decoder structure with a Transformer module to enhance global context extraction, a U-shaped full-scale feature extraction module to preserve multiscale spatial details, and a convolutional decoder for effective feature fusion and resolution restoration. …”
Get full text

Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer by Ruowu Wu, Yandan Liang, Lianlei Lin, Zongwei Zhang

“…After that, in order to ensure that the model has better prediction ability for global and local hotspot areas, we designed a composite loss function based on MSE and SSIM to focus on the global and structural distribution of weather to achieve more accurate multivariate weather prediction. …”
Get full text

GKCAE: A graph-attention-based encoder for fine-grained semantic segmentation of high-voltage transmission corridors scenario LiDAR data by Su Zhang, Haibo Liu, Jingguo Rong, Yaping Zhang

“…GKCAE first captures local geometric features using Kernel Point Convolution, and then models inter-class spatial relationships through Graph Edge-Conditioned Convolution to incorporate global contextual information. …”
Get full text

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. …”
Get full text

Multi-scale window transformer for cervical cytopathology image recognition by Jiaxiang Yi, Xiuli Liu, Shenghua Cheng, Li Chen, Shaoqun Zeng

Get full text