Satellite Image Classification using semantic segmentation methods in deep learning

Satellite images classification

Satellite Image Analytics and Earth Data Science Experiments in Python

Classifying SAT-6 data using a CNN

Few-shot satellite image classification for bringing deep learning on board OPS-SAT

The application of various CNNs on an Aid dataset for satellite image classification.

This repository will guide you how to use deep learning algorithms for land use land cover classification using satellite dataset!

This repository provides the training codes to classify aerial images using a custom-built model (transfer learning with InceptionResNetV2 as the backbone) and explainers to explain the predictions with LIME and GradCAM on an interface that lets you upload or paste images for classification and see visual explanations.

Satellite Image Classification

This repository contains code for building a deep learning model to classify satellite images into different categories such as Cloudy, Desert, Green Area, and Water.

DL model deployment using docker, API deployment with FastAPI, and MLOps using WandB for overhead-mnist dataset