In this brief, we consider the problem of descriptors construction for the task of content-based
image retrieval using deep neural networks. The idea of neural codes, based on fully …

This paper introduces a plug-and-play descriptor that can be effectively adopted for image
retrieval tasks without prior initialization or preparation. The description method utilizes the …

Nowadays, the use of Convolutional Neural Networks (CNNs) has led to tremendous
achievements in several computer vision challenges. CNN-based image retrieval methods …

Abstract CNN (Convolution Neural Network)-based descriptor generation is extensively
studied recently for image retrieval. CNN deep feature trained for image classification is …

Image retrieval is a challenging task of searching images similar to the query one from a
database. Previous learning-based methods adopt various ingenious designs to increase …

Image search can be tackled using deep features from pre-trained Convolutional Neural
Networks (CNN). The feature map from the last convolutional layer of a CNN encodes …

Several recent works have shown that image descriptors produced by deep convolutional
neural networks provide state-of-the-art performance for image classification and retrieval …

Applying deep convolutional features to image retrieval has become the mainstream method
in the field of image retrieval. However, the discriminative power of deep convolutional …

Currently, visual sensors are becoming increasingly affordable and fashionable,
acceleratingly the increasing number of image data. Image retrieval has attracted increasing …

This paper addresses the problem of large scale image retrieval, with the aim of accurately
ranking the similarity of a large number of images to a given query image. To achieve this …