A New Method for Improving Content-Based Image Retrieval using Deep Learning

In this work we will show a novel method for improving the performance of content-based image retrieval using a deep neural network. The main focus of the method is training the distance function using the deep neural network and transfer learning. An existing pretrained network for image classification is used as a basis. One of the method's benefits is the fact that the existing network is not retrained and features for the distance function are the neural network's layers which were trained and stored before. The method is tested with the publicly available VGG19 deep neural network. Obtained results are comparable or in some cases better than the state of the art methods with a similar approach.