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: cnn
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 see how deep learning techniques (Recurrent Neural Network, RNN and/or Convolutional Neural Network, CNN) can be used to determine the sentiment polarity of a written text. This is call "sentiment analysis" and it's very useful to enhanced the communication with your customers. Such algorithms are typically used to analyze emails, website or even Facebook posts where your customers may talk about your products. Thanks to this, you can prioritize your answers and react faster to the unsatisfied customers... ...