Thus, we propose a Spatial Multiscale Interactive Fusion MAM Recognition Network to solve the difficulties in MAM recognition. First, this paper presents an optical flow‐based hand motion contour global feature extraction method for acupuncture hand shape. Second, to explore the m...
Wei et al. formulated an interactive visual model that uses self-interaction, mutual interaction, multi-interaction, and adaptive interaction, forming the first interactive completeness of the visual interaction network. We also employ the adaptive adjustment mechanism to enhance the performance of the ...
Attention-based interactive multi-level feature fusion for named entity recognition Article Open access 24 January 2025 BioBBC: a multi-feature model that enhances the detection of biomedical entities Article Open access 02 April 2024 Introduction With the development of online social platforms, a...
Therefore, adding multiscale spatial interactive navigation to VEs can effectively enhance the user experience in a large virtual world. The spatial navigation functions in an MSVE enable users to observe the structure and organization of VEs and locate and navigate them on demand. This allows ...
Magnetospheric Multiscale Instrument Suite Operations and Data System 9 Conclusion 573 The MMS mission features burst data that have cadences that can resolve the electron dif- fusion region in magnetic reconnection. The burst data volume, however, far exceeds the bandwidth of the MMS telemetry ...
Secondly, the interactive attention mechanism (IA) was proposed to enhance the deep characteristics of multivariate fatty acids from the fusion of two dimensions, so that the model paid more attention to the subtle differences between different processes, and effectively solved the problem of fuzzy ...
To this end, this paper proposes a dual-branch grouping multiscale residual embedding U-Net and cross-attention fusion networks (DGMRU_CAF) for hyperspectral image classification is proposed. The network contains two branches, spatial GMRU and spectral GMRU, which can reduc...
Jupyter notebooks for interactive visualization and correction of the predicted segmentation are also part of the framework and added onto the GitHub, which allows improving the model accuracy with minimal annotating time. To check whether this approach was valid, we compared the trained network output...
In this paper, we propose a processing mechanism based on a balanced attention module and interactive residual module. The mechanism addressed the acquisition of the multiscale features by capturing shallow and deep context information. For effective information fusion, a modified bi-directional ...
However, most of the existing methods adopt simple fusion mechanisms, which fail to utilize the complementary information between modalities while lacking the guidance of a priori knowledge. To address the above issues, we propose a novel background-aware cross-attention multiscale fusion network (BA...