Feature extraction and similarity measurement are two key steps in image retrieval. AlexNet
is a classical deep convolutional neural network for image classification, but using it directly …

The proliferation of mobile devices is producing a new wave of mobile visual search
applications that enable users to sense their surroundings with smart phones. As the …

Hashing methods have proven to be effective in the field of large-scale image retrieval. In
recent years, the performance of hashing algorithms based on deep learning has greatly …

In this paper, we propose a nonlinear discrete hashing approach to learn compact binary
codes for scalable image search. Instead of seeking a single linear projection in most …

This work proposes a privacy-protection framework for an important application called
outsourced media search. This scenario involves a data owner, a client, and an untrusted …

We present PSEUDo, a visual pattern retrieval tool for multivariate time series. It aims to
overcome the uneconomic (re-) training problem accompanying deep learning-based …

To facilitate fast similarity search, this paper proposes to encode the nonlinear similarity and
image structure as compact binary codes. Rather than adopting single matrix as projection …

A hash algorithm converts data into compact strings. In the multimedia domain, effective
hashing is the key to large-scale similarity search in high-dimensional feature space. A limit …

240 Big Data Analytics for Large-Scale Multimedia Search hash algorithms, it can be more
efficient and effective to combine existing algorithms instead of designing new ones from …

Deep learning technology has been introduced into many multimedia processing tasks,
including multimedia retrieval. In this paper, we propose a deep residual net (ResNet) based …