This paper presents a comprehensive survey examining the prevailing feature extraction
methodologies employed within biometric palmprint recognition models. It encompasses a …

Few-shot image classification aims at learning a model from previous experiences that can
be rapidly adapted to classify images of new classes with a few labeled examples. The …

Palmprint recognition is one of the most popular biometric technologies. Recent researches
mainly focus on the recognition performance, while pay less attention to the data protection …

Unconstrained Palmprint Recognition (UPR) shows engaging potential owing to its high
hygiene and privacy. The unconstrained acquisition usually produces wide variations …

Palmprint identification aims to establish the identity of a given query sample by comparing it
with all the templates in the database and locating the most similar one. It becomes …

Research on palmprint recognition has been progressing toward a contactless and
unconstrained direction, where the imaging quality is easily disturbed by various factors …

Robustness enhancement and feature selection are the two crucial issues to be resolved in
robust palmprint recognition. However, existing regression-based methods are insufficient to …

As a type of biometric recognition, palmprint recognition uses unique discriminative features
on the palm of a person to identify his/her identity. It has attracted much attention because of …

Palmprint recognition techniques have been widely applied in security authentication. As a
typical image processing method, convolutional neural network (CNN) has been applied to …

In this paper, we tackle the few-shot learning problem in a semi-supervised setting where a
limited number of labeled data-points and a number of low-cost unlabeled samples are …