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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 11–20 of 33 papers

TitleStatusHype
Diagnosing Model Performance Under Distribution ShiftCode0
Improving Human-AI Collaboration With Descriptions of AI Behavior—0
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image ClassificationCode2
Data Generation for Satellite Image Classification Using Self-Supervised Representation Learning—0
2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips—0
Out-of-distribution detection in satellite image classification—0
Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image ClassificationCode1
Satellite Image Classification with Deep Learning—0
Classification and understanding of cloud structures via satellite images with EfficientUNetCode1
SpinalNet: Deep Neural Network with Gradual InputCode1
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