Remote Sensing Image Classification
30 papers with code • 1 benchmarks • 8 datasets
Datasets
AID
Million-AID
WHU-RS19
OpenStreetMap Multi-Sensor Scene Classification
FireRisk
RTI Rwanda Drone Crop Types
Latest papers
FlightScope: A Deep Comprehensive Assessment of Aircraft Detection Algorithms in Satellite Imagery
Object detection in remotely sensed satellite pictures is fundamental in many fields such as biophysical, and environmental monitoring.
RSMamba: Remote Sensing Image Classification with State Space Model
KyanChen/RSMamba
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Remote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation.
ViGEO: an Assessment of Vision GNNs in Earth Observation
lccol/vig-eo
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Satellite missions and Earth Observation (EO) systems represent fundamental assets for environmental monitoring and the timely identification of catastrophic events, long-term monitoring of both natural resources and human-made assets, such as vegetation, water bodies, forests as well as buildings.
SS-MAE: Spatial-Spectral Masked Auto-Encoder for Multi-Source Remote Sensing Image Classification
summitgao/ss-mae
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Existing MIM-based methods mostly focus on spatial feature modeling, neglecting spectral feature modeling.
DGCNet: An Efficient 3D-Densenet based on Dynamic Group Convolution for Hyperspectral Remote Sensing Image Classification
leeguandong/DGCNet-for-HSI
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Referring to the idea of dynamic network, dynamic group convolution(DGC) is designed on 3d convolution kernel.
Quantitative Analysis of Primary Attribution Explainable Artificial Intelligence Methods for Remote Sensing Image Classification
We present a comprehensive analysis of quantitatively evaluating explainable artificial intelligence (XAI) techniques for remote sensing image classification.
FireRisk: A Remote Sensing Dataset for Fire Risk Assessment with Benchmarks Using Supervised and Self-supervised Learning
Inspired by the abundance of publicly available remote sensing projects and the burgeoning development of deep learning in computer vision, our research focuses on assessing fire risk using remote sensing imagery.
Universal Domain Adaptation for Remote Sensing Image Scene Classification
zhu-xlab/unida
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Empirical results show that the proposed model is effective and practical for remote sensing image scene classification, regardless of whether the source data is available or not.
Semantic Interleaving Global Channel Attention for Multilabel Remote Sensing Image Classification
kyle-one/signa
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First, the label co-occurrence graph is obtained according to the statistical information of the data set.
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification
We present AiTLAS: Benchmark Arena -- an open-source benchmark suite for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO).
