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 with no code
Nearest Neighbor Based Out-of-Distribution Detection in Remote Sensing Scene Classification
In this paper we deal with the problem of detecting remote sensing images coming from a different distribution compared to the training data - out of distribution images.
MMFormer: Multimodal Transformer Using Multiscale Self-Attention for Remote Sensing Image Classification
To benefit the complementary information between heterogeneous data, we introduce a new Multimodal Transformer (MMFormer) for Remote Sensing (RS) image classification using Hyperspectral Image (HSI) accompanied by another source of data such as Light Detection and Ranging (LiDAR).
A Light-weight Deep Learning Model for Remote Sensing Image Classification
In this paper, we present a high-performance and light-weight deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the aerial scene of a remote sensing image.
Example-Based Explainable AI and its Application for Remote Sensing Image Classification
We present a method of explainable artificial intelligence (XAI), "What I Know (WIK)", to provide additional information to verify the reliability of a deep learning model by showing an example of an instance in a training dataset that is similar to the input data to be inferred and demonstrate it in a remote sensing image classification task.
DDIPNet and DDIPNet+: Discriminant Deep Image Prior Networks for Remote Sensing Image Classification
Research on remote sensing image classification significantly impacts essential human routine tasks such as urban planning and agriculture.
A Robust and Low Complexity Deep Learning Model for Remote Sensing Image Classification
In this paper, we present a robust and low complexity deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the scene of a remote sensing image.
On the Effects of Different Types of Label Noise in Multi-Label Remote Sensing Image Classification
In this paper, we investigate three different noise robust CV SLC methods and adapt them to be robust for multi-label noise scenarios in RS.
Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network
The task of remote sensing image scene classification (RSISC), which aims at classifying remote sensing images into groups of semantic categories based on their contents, has taken the important role in a wide range of applications such as urban planning, natural hazards detection, environment monitoring, vegetation mapping, or geospatial object detection.
Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification
In this work, we use for HSRS image classification a special class of deep neural networks, namely a Bayesian neural network (BNN).
Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives
Therefore, remote sensing image understanding often faces the problems of incomplete, inexact, and inaccurate supervised information, which will affect the breadth and depth of remote sensing applications.
