Channel2DTransformer: A Multi-level Features Self-attention Fusion Module for Semantic Segmentation
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Channel2DTransformer: A Multi-level Features Self-attention Fusion Module for Semantic Segmentation ; volume:17 ; number:1 ; day:18 ; month:11 ; year:2024 ; pages:1-11 ; date:12.2024
International journal of computational intelligence systems ; 17, Heft 1 (18.11.2024), 1-11, 12.2024
- Urheber
-
Liu, Weitao
Wu, Junjun
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s44196-024-00630-5
- URN
-
urn:nbn:de:101:1-2502042116151.154586406807
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:33 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Liu, Weitao
- Wu, Junjun
- SpringerLink (Online service)
Ähnliche Objekte (12)
Semantic segmentation-assisted instance feature fusion for multi-level 3D part instance segmentation
Global–Local Query-Support Cross-Attention for Few-Shot Semantic Segmentation
Nested attention network based on category contexts learning for semantic segmentation
TCANet: three-stream coordinate attention network for RGB-D indoor semantic segmentation
Channel Attention Module for Segmentation of 3D Hyperspectral Point Clouds in Geological Applications
Brain tumor image segmentation method using hybrid attention module and improved mask RCNN
MADR-Net: multi-level attention dilated residual neural network for segmentation of medical images
Semantic Segmentation of Ambiguous Images
Semantic segmentation of textured mosaics
Sfnet: Faster and Accurate Semantic Segmentation Via Semantic Flow
NA-segformer: A multi-level transformer model based on neighborhood attention for colonoscopic polyp segmentation
JSMNET: IMPROVING INDOOR POINT CLOUD SEMANTIC AND INSTANCE SEGMENTATION THROUGH SELF-ATTENTION AND MULTISCALE FUSION
Semantic segmentation-assisted instance feature fusion for multi-level 3D part instance segmentation
Global–Local Query-Support Cross-Attention for Few-Shot Semantic Segmentation
Nested attention network based on category contexts learning for semantic segmentation
TCANet: three-stream coordinate attention network for RGB-D indoor semantic segmentation
Channel Attention Module for Segmentation of 3D Hyperspectral Point Clouds in Geological Applications
Brain tumor image segmentation method using hybrid attention module and improved mask RCNN
MADR-Net: multi-level attention dilated residual neural network for segmentation of medical images
Semantic Segmentation of Ambiguous Images
Semantic segmentation of textured mosaics
Sfnet: Faster and Accurate Semantic Segmentation Via Semantic Flow
NA-segformer: A multi-level transformer model based on neighborhood attention for colonoscopic polyp segmentation
JSMNET: IMPROVING INDOOR POINT CLOUD SEMANTIC AND INSTANCE SEGMENTATION THROUGH SELF-ATTENTION AND MULTISCALE FUSION
Semantic segmentation-assisted instance feature fusion for multi-level 3D part instance segmentation
Global–Local Query-Support Cross-Attention for Few-Shot Semantic Segmentation
Nested attention network based on category contexts learning for semantic segmentation
TCANet: three-stream coordinate attention network for RGB-D indoor semantic segmentation
Channel Attention Module for Segmentation of 3D Hyperspectral Point Clouds in Geological Applications
Brain tumor image segmentation method using hybrid attention module and improved mask RCNN
MADR-Net: multi-level attention dilated residual neural network for segmentation of medical images
Semantic Segmentation of Ambiguous Images
Semantic segmentation of textured mosaics
Sfnet: Faster and Accurate Semantic Segmentation Via Semantic Flow
NA-segformer: A multi-level transformer model based on neighborhood attention for colonoscopic polyp segmentation