SOTAVerified

Land Cover Classification

Papers

Showing 1–25 of 151 papers

TitleStatusHype
Baltimore Atlas: FreqWeaver Adapter for Semi-supervised Ultra-high Spatial Resolution Land Cover Classification—0
Beyond Pretty Pictures: Combined Single- and Multi-Image Super-resolution for Sentinel-2 Images—0
HyperPointFormer: Multimodal Fusion in 3D Space with Dual-Branch Cross-Attention TransformersCode0
Supervised and self-supervised land-cover segmentation & classification of the Biesbosch wetlands—0
Generalizable Multispectral Land Cover Classification via Frequency-Aware Mixture of Low-Rank Token Experts—0
HyperspectralMAE: The Hyperspectral Imagery Classification Model using Fourier-Encoded Dual-Branch Masked Autoencoder—0
Prototype-Based Information Compensation Network for Multi-Source Remote Sensing Data ClassificationCode0
Core-Set Selection for Data-efficient Land Cover SegmentationCode0
PAD: Phase-Amplitude Decoupling Fusion for Multi-Modal Land Cover ClassificationCode0
Geographical Context Matters: Bridging Fine and Coarse Spatial Information to Enhance Continental Land Cover MappingCode0
SAR-to-RGB Translation with Latent Diffusion for Earth Observation—0
FlexiMo: A Flexible Remote Sensing Foundation Model—0
A Survey on Remote Sensing Foundation Models: From Vision to MultimodalityCode2
Uncertainty-aware Bayesian machine learning modelling of land cover classification—0
CerraData-4MM: A multimodal benchmark dataset on Cerrado for land use and land cover classificationCode0
ASANet: Asymmetric Semantic Aligning Network for RGB and SAR image land cover classificationCode0
Pattern Integration and Enhancement Vision Transformer for Self-Supervised Learning in Remote Sensing—0
Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation—0
SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image SegmentationCode1
DDU-Net: A Domain Decomposition-Based CNN for High-Resolution Image Segmentation on Multiple GPUsCode0
Evaluating and Benchmarking Foundation Models for Earth Observation and Geospatial AI—0
Improving EO Foundation Models with Confidence Assessment for enhanced Semantic segmentationCode0
Evaluation of Deep Learning Semantic Segmentation for Land Cover Mapping on Multispectral, Hyperspectral and High Spatial Aerial Imagery—0
AGBD: A Global-scale Biomass DatasetCode1
Global High Categorical Resolution Land Cover Mapping via Weak Supervision—0
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