In this paper, we propose a novel model for seizure prediction that incorporates a convolutional neural network (CNN) with multi-head attention mechanism. In this model, the shallow CNN automatically captures the EEG features, and the multi-headed attention focuses on discriminating the effective ...
transformer design, which enables the model to efficiently collect the contextual information in the sequence by utilizing the multi-headed attention mechanism... X Liu,S Qiao,T Zhang,... - 《Digital Signal Processing》 被引量: 0发表: 2024年 Foldable Musical Instrument Stand and Multi-headed Mu...
Subsequently, we utilize the long-distance capturing capability of the multi-head attention mechanism to obtain the contextual relationships among the relevant packets in the cuflow and the inline relationships among the packet payloads. To verify the effectiveness and generality of CUFT across various...
The self-attention-based vision transformer has powerful feature extraction capabilities and has demonstrated competitive performance in several tasks. However, the conventional self-attention mechanism that exhibits global perceptual properties while favoring large-scale objects, room for improvement still ...
In this paper, we use a parallel multi-scale feature extraction module based on graph convolution and an upsampling method with an added multi-head attention mechanism to process sparse and irregular point cloud data to obtain extended point clouds. Specifically, a point cloud...
In this paper, we propose ConvFormer, a novel convolutional transformer that leverages a new dynamic multi-headed convolutional self-attention mechanism for monocular 3D human pose estimation. We designed a spatial and temporal convolutional transformer to comprehensively model human joint relations within...
SST-YOLOv5s: advancing real-time blood cell object detection through multi-headed attention mechanismdoi:10.1007/s11760-024-03788-9Deep learningMedical image processBlood cellYOLOv5sObject detectionAn important method of diagnosing diseases in medicine is the examination of blood samples in which the ...
The global features of the input image were obtained using a multi-headed self-attention mechanism, and then fused with the local features extracted by CNN to obtain a fused feature. In addition, a shifting window calculation was used to reduce the computational effort when calculating the self-...