  Evaluating aesthetic value of digital photographs is a challenging task,
mainly due to numerous factors that need to be taken into account and
subjective manner of this process. In this paper, we propose to approach this
problem using deep convolutional neural networks. Using a dataset of over 1.7
million photos collected from Flickr, we train and evaluate a deep learning
model whose goal is to classify input images by analysing their aesthetic
value. The result of this work is a publicly available Web-based application
that can be used in several real-life applications, e.g. to improve the
workflow of professional photographers by pre-selecting the best photos.
