Archives May 2017

In this blog post, we will see how we can use reverse image search based on (unsupervised) convolutional neural networks to make the analysis of satellite/aerial pictures both more efficient and simpler. After reading this post, you will be able to find similar objects in a large aerial/satellite images and from there develop your own GIS statistical applications (i.e. to count all white cars in your neighborhood, identify specific road markings or kind of trees, etc. ).

The requirement for a (very) large training set is generally the main criticism that is formulated against deeplearning algorithms. In this blog, we show, how deep convolutional neural networks (CNN) can be used in an unsupervised manner to perform efficient reverse image search.