The need for appropriate ways to measure the distance or similarity between data is
ubiquitous in machine learning, pattern recognition and data mining, but handcrafting such …

Abstract The goal of Facial Kinship Verification (FKV) is to automatically determine whether
two individuals have a kin relationship or not from their given facial images or videos. It is an …

This paper presents a new discriminative deep metric learning (DDML) method for face and
kinship verification in wild conditions. While metric learning has achieved reasonably good …

Conventional metric learning methods usually assume that the training and test samples are
captured in similar scenarios so that their distributions are assumed to be the same. This …

This paper presents a sharable and individual multi-view metric learning (MvML) approach
for visual recognition. Unlike conventional metric leaning methods which learn a distance …

In this paper, we propose a new discriminative multimetric learning method for kinship
verification via facial image analysis. Given each face image, we first extract multiple …

Metric learning has attracted increasing attention due to its critical role in image analysis and
classification. Conventional metric learning always assumes that the training and test data …

Clustering by fast search and find of density peaks (CFSFDP) is a novel algorithm that
efficiently discovers the centers of clusters by finding the density peaks. The accuracy of …

This research work aims to propose an effective and robust face kinship verification system
by leveraging several axes, including advanced learning techniques, deep learning, and …

We propose a completely automatic approach for recognizing low resolution face images
captured in uncontrolled environment. The approach uses multidimensional scaling to learn …