Remote Sensing Image Classification
33 papers with code • 1 benchmarks • 9 datasets
Datasets
AID
Million-AID
WHU-RS19
FireRisk
DRIFT
OpenStreetMap Multi-Sensor Scene Classification
RTI Rwanda Drone Crop Types
Most implemented papers
Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network
Jakaria08/Filter_Enhance_Detect
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Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we apply a new edge-enhanced super-resolution GAN (EESRGAN) to improve the image quality of remote sensing images and use different detector networks in an end-to-end manner where detector loss is backpropagated into the EESRGAN to improve the detection performance.
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.
Lake Ice Monitoring with Webcams and Crowd-Sourced Images
czarmanu/deeplab-lakeice-webcams
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On average, it achieves intersection-over-union (IoU) values of ~71% across different cameras and ~69% across different winters, greatly outperforming prior work.
Multimodal Fusion Transformer for Remote Sensing Image Classification
ankurderia/mft
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Vision transformers (ViTs) have been trending in image classification tasks due to their promising performance when compared to convolutional neural networks (CNNs).
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).
MSFMamba: Multi-Scale Feature Fusion State Space Model for Multi-Source Remote Sensing Image Classification
The MSFMamba network is composed of three key components: the Multi-Scale Spatial Mamba (MSpa-Mamba) block, the Spectral Mamba (Spe-Mamba) block, and the Fusion Mamba (Fus-Mamba) block.
RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data
In this paper, we propose a remote sensing image classification benchmark (RSI-CB) based on massive, scalable, and diverse crowdsource data.
LAKE ICE MONITORING WITH WEBCAMS
czarmanu/tiramisu_keras
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ISPRS annals of the photogrammetry, remote sensing and spatial information sciences 2018
Continuous monitoring of climate indicators is important for understanding the dynamics and trends of the climate system.
Wide Contextual Residual Network with Active Learning for Remote Sensing Image Classification
codeRimoe/DL_for_RSIs
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IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium 2018
As it is very difficult and expensive to obtain class labels in real world, we integrate the proposed WCRN with AL to improve its generalization by using the most informative training samples.
Lake Ice Detection from Sentinel-1 SAR with Deep Learning
Lake ice, as part of the Essential Climate Variable (ECV) lakes, is an important indicator to monitor climate change and global warming.
