Introduction The introduction of AlexNet back in 2012 can be considered one of the breakthrough events that triggered the ongoing evolution of the deep learning (DL) subdomain of artificial intelligence. In that year, AlexNet greatly outperformed competing algorithms by a… Read More »A Brief Overview of AI-driven Image Analysis
Introduction In a series of earlier posts, we have discussed how geospatial imagery can be segmented using a deep neural network. When applying such a trained model to imagery data, noise is a common and often not desirable phenomenon. Figure… Read More »Noise Removal with Connected Components Analysis using GDAL and OpenCV
Introduction In the previous post, we have defined the U-Net architecture and defined a class to access our training samples. Hence, we are ready to train the model. This first requires to split up our image crops into different datasets… Read More »Semantic Segmentation of Geospatial Imagery with Deep Learning Part 5 – Training the Model
Introduction In the previous post, we have successfully created image crops that we are going to use for training the U-Net model. In this post, we are going to talk about how the U-Net architecture looks like and how it… Read More »Semantic Segmentation of Geospatial Imagery with Deep Learning Part 4 – U-Net
Introduction In the previous post of this series, we have acquired the relevant datasets and transformed the lake vector dataset into a raster file that aligns with the SWISSIMAGE dataset. In this blog post, we are going to use these… Read More »Semantic Segmentation of Geospatial Imagery with Deep Learning Part 3 – Training Samples
Introduction In the previous post, we have set up our working environment. In this blog post, we are going to have a look at from where we can obtain suitable training datasets. Training a deep learning model is only possible… Read More »Semantic Segmentation of Geospatial Imagery with Deep Learning Part 2 – Data Acquisition
Introduction Feature segmentation, i.e., the association of a pixel to a certain feature class such as a tree or a car, is a common task when processing remote sensing data. In recent years, this task has been dominated by deep… Read More »Semantic Segmentation of Geospatial Imagery with Deep Learning Part 1 – Setup