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MFFNet: Image Semantic Segmentation Network of Multi-level Feature Fusion

Jisuanji kexue yu tansuo, 2024-03, Vol.18 (3), p.707-717 [Peer Reviewed Journal]

ISSN: 1673-9418 ;DOI: 10.3778/j.issn.1673-9418.2209110

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  • Title:
    MFFNet: Image Semantic Segmentation Network of Multi-level Feature Fusion
  • Author: WANG Yan, NAN Peiqi
  • Subjects: encoder-decoder; context information; spatial information; feature fusion
  • Is Part Of: Jisuanji kexue yu tansuo, 2024-03, Vol.18 (3), p.707-717
  • Description: In the task of image semantic segmentation, most methods do not make full use of features of different scales and levels, but directly upsampling, which will cause some effective information to be dismissed as redundant information, thus reducing the accuracy and sensitivity of segmentation of some small categories and similar categories. Therefore, a multi-level feature fusion network (MFFNet) is proposed. MFFNet uses encoder-decoder structure, during the encoding stage, the context information and spatial detail information are obtained through the context information extraction path and spatial information extraction path respectively to enhance the inter-pixel correlation and boundary accuracy. During the decoding stage, a multi-level feature fusion path is designed, and the context information is fused by the mixed bilateral fusion module. Deep information and spatial information are fused by high-low feature fusion module. The global channel-attention fusion module is used to obtain the connections betw
  • Publisher: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
  • Language: Chinese
  • Identifier: ISSN: 1673-9418
    DOI: 10.3778/j.issn.1673-9418.2209110
  • Source: DOAJ Directory of Open Access Journals
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