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Satellite Image Classification

Satellite image classification is the most significant technique used in remote sensing for the computerized study and pattern recognition of satellite information, which is based on diversity structures of the image that involve rigorous validation of the training samples depending on the used classification algorithm.

Papers

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Showing 1–25 of 33 papers

TitleStatusHype
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image ClassificationCode2
An Open-source Tool for Hyperspectral Image Augmentation in TensorflowCode1
FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite ImageryCode1
Reduction of Class Activation Uncertainty with Background InformationCode1
SpinalNet: Deep Neural Network with Gradual InputCode1
Classification and understanding of cloud structures via satellite images with EfficientUNetCode1
Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image ClassificationCode1
Diagnosing Model Performance Under Distribution ShiftCode0
Discriminative Learning of Deep Convolutional Feature Point DescriptorsCode0
Kolmogorov-Arnold Network for Satellite Image Classification in Remote SensingCode0
Improving Power Plant CO2 Emission Estimation with Deep Learning and Satellite/Simulated DataCode0
Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT ModelsCode0
Practical insights on the effect of different encodings, ansätze and measurements in quantum and hybrid convolutional neural networksCode0
Deep Ensembling of Multiband Images for Earth Remote Sensing and Foramnifera DataCode0
DeepSat - A Learning framework for Satellite ImageryCode0
DeepSat V2: Feature Augmented Convolutional Neural Nets for Satellite Image ClassificationCode0
An Effective Weight Initialization Method for Deep Learning: Application to Satellite Image ClassificationCode0
Using satellite image classification and digital terrain modelling to assess forest species distribution on mountain slopes.A case study in Varatec Forest District—0
Adversarial Examples in Remote Sensing—0
Data Generation for Satellite Image Classification Using Self-Supervised Representation Learning—0
Morphological Network: How Far Can We Go with Morphological Neurons?—0
Improving Human-AI Collaboration With Descriptions of AI Behavior—0
Learning Multi-Scale Deep Features for High-Resolution Satellite Image Classification—0
Out-of-distribution detection in satellite image classification—0
predictSLUMS: A new model for identifying and predicting informal settlements and slums in cities from street intersections using machine learning—0
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