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. ).
Tag archives: deep-learning
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.
In this blog, we will finally give an answer to THE question: R, Python, Scala, Spark, Tensorflow, etc... What is the best one to answer data science questions? The question itself is totally absurd, but they are so many people asking it on social network that we find it worth to finally answer the recurrent question using a scientific methodology. At the end of this blog, you will find a quantitative answer comparing the computing time of each language/library for fitting the exact same Generalized Linear Model (GLM). Many features matter in the choice of a language/library, among them , the computing and developing time are for sure very important criteria....