From Pixels to Images: A Structural Survey of Deep Learning Paradigms in Remote Sensing Image Semantic Segmentation
cs.CV
Submitted: 2025-05-21
Updated: 2026-09-15
Terminology
Sources
- Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery
- CM-UNet: Hybrid CNN-Mamba UNet for Remote Sensing Image Semantic Segmentation
- A Universal Knowledge Embedded Contrastive Learning Framework for Hyperspectral Image Classification
- S4DL: Shift-sensitive Spatial-Spectral Disentangling Learning for Hyperspectral Image Unsupervised Domain Adaptation
- HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model
- SpectralX: Parameter-efficient Domain Generalization for Spectral Remote Sensing Foundation Models
- CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic Segmentation
- Incomplete Multimodal Learning for Remote Sensing Data Fusion
- MoSAiC: Multi-Modal Multi-Label Supervision-Aware Contrastive Learning for Remote Sensing
- Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation
- SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model
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