Author - Anna Sheptalina

Classification of image style using deep learning with Python

In this article, I want to talk about the use of convolutional neural networks for the classification of images by style.

The goal of our project is to build software to identify whether an image is in the “BMW style”. In other words, we are faced with the task of classifying images. It is important to note here that images could be of any content, with and without cars. So, the main interest here is not to identify a car object, or identify a BMW car, rather identify a BMW look and feel – colors, composition and so on. But we can’t select these attributes of style manually. To solve this problem, it was proposed to use a neural network, in which such complex features will be found automatically in the learning process.

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Apache Solr and the great features it provides

In this article we will look at the main features of the search engine Solr. Apache Solr is a powerful tool with an amazing search capability.

Introduction

The need to use full-text search today is conditioned by the need to search information in the ever-increasing number of electronic documents. It is very important to be able to quickly find the necessary information among them, so many applications today use various full-text search engines.
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