Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 17, 2024Remote SensingOpen Access

A Novel Mamba Architecture with a Semantic Transformer for Efficient Real-Time Remote Sensing Semantic Segmentation

View Full Paper
Ask AI
Bookmark
Share

Authors

HDHao DingLinyi UniversityBXBo XiaUniversity Town of ShenzhenWLWeilin LiuChina Academy of Space Technology

Discussion

Loading...

Member takes

Implication

Key Points

Key points are not available for this paper at this time.

Cite This Study

Ding et al. (2024) studied this question.

synapsesocial.com/papers/68e5fef1b6db643587592d3ehttps://doi.org/10.3390/rs16142620
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1ImageNet classification with deep convolutional neural networks2017 · 109,542 citations
  2. 2SCTNet: Single-Branch CNN with Transformer Semantic Information for Real-Time Segmentation2024 · 180 citations
  3. 3Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review2020 · 1,228 citations
  4. 4RSMamba: Remote Sensing Image Classification With State Space Model2024 · 351 citations
  5. 5LSRFormer: Efficient Transformer Supply Convolutional Neural Networks With Global Information for Aerial Image Segmentation2024 · 40 citations