Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

The accuracies for many pattern recognition tasks have increased rapidly year by year,
achieving or even outperforming human performance. From the perspective of accuracy …

Recently, multi-view representation learning has become a rapidly growing direction in
machine learning and data mining areas. This paper introduces two categories for multi …

Abstract recommendation, and marketing services. Extensive efforts have been made to
conquer the cross-modal retrieval problem in the general domain. When it comes to E …

Information fusion is a key step in multimodal biometric systems. The fusion of information
can occur at different levels of a recognition system, ie, at the feature level, matching-score …

This paper presents a new discriminative deep metric learning (DDML) method for face
verification in the wild. Different from existing metric learning-based face verification …

In this paper, we address the text and image matching in cross-modal retrieval of the fashion
industry. Different from the matching in the general domain, the fashion matching is required …

This paper presents a general multi-view feature extraction approach that we call
Generalized Multiview Analysis or GMA. GMA has all the desirable properties required for …

Cross-modal retrieval has recently drawn much attention due to the widespread existence of
multimodal data. It takes one type of data as the query to retrieve relevant data objects of …

Multi-modal clustering (MMC) aims to explore complementary information from diverse
modalities for clustering performance facilitating. This article studies challenging problems in …