Neural Network for Satellite Data Classification Using Tensorflow in Python -> A step-by-step guide for Landsat 5 multispectral data classification for binary built-up/non-built-up class prediction, with repo.Detecting deforestation from satellite images -> using FastAI and ResNet50, with repo fsdl_deforestation_detection.
Land Cover Classification of Satellite Imagery using Convolutional Neural Networks using Keras and a multi spectral dataset captured over vineyard fields of Salinas Valley, California.Land-Cover-Classification-using-Sentinel-2-Dataset -> well written Medium article accompanying this repo but using the EuroSAT dataset.Detecting Informal Settlements from Satellite Imagery using fine-tuning of ResNet-50 classifier with repo.Multi-Label Classification of Satellite Photos of the Amazon Rainforest using keras or FastAI 🔰.Also checkout Multi-label Land Cover Classification using the redesigned multi-label Merced dataset with 17 land cover classes 🔰 Land Use Classification on Merced dataset using CNN in Keras.Land classification on Sentinel 2 data using a simple sklearn cluster algorithm or deep learning CNN 🔰.Read my blog post A brief introduction to satellite image classification with neural networks This approach of image level classification is not to be confused with pixel-level classification which is called semantic segmentation.
The more complex case is applying multiple labels to an image. The classic cats vs dogs image classification task, which in the remote sensing domain is used to assign a label to an image, e.g. Good background reading is Deep learning in remote sensing applications: A meta-analysis and review Classification This section explores the different deep and machine learning (ML) techniques applied to common problems in satellite imagery analysis. Terrain mapping, Disparity Estimation, Lidar, DEMs & NeRF.Self-supervised, unsupervised & contrastive learning.Image Captioning & Visual Question Answering.Autoencoders, dimensionality reduction, image embeddings & similarity search.Oil storage tank detection & oil spills.Object detection enhanced by super resolution.Object detection with rotated bounding boxes.Material that is suitable for getting started with a topic is tagged with the 🔰 emoji, which can also be searched. Otherwise refer to the table of contents below, and search within the relevant section. a dataset name) you can Control+F to search for it in the page.
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How to use this repository: if you know exactly what you are looking for (e.g. If this resource is useful to your work please consider sponsoring it with a donation via Github Sponsors You can follow me on Twitter and join the dedicated satellite-image-deep-learning group on LinkedIn. To a lesser extent classical machine learning techniques are listed, as are topics such as cloud computing and model deployment. This repository lists resources on the topic of deep learning applied to satellite and aerial imagery.
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