… This solution is toward an effective palmprint recognition system that can be realized later
in this paper. The process is visualized in the figures using PolyU image data. …

… method to jointly learn compact multifeature codes (LCMFCs) for palmprint recognition
with a single training sample per palm. Unlike most existing hand-crafted methods that extract …

… palmprint recognition method based on eigenspace technology. By means of the
Karhunen–Loeve transform, the original palmprint … Let the training samples of the palmprint …

… Typically, these endto-end training relies on large amount of supervised training epochs to
… many training samples carefully. When we build a large-scale palmprint recognition system, …

… III Experiment 3 The number of training samples In the field of image recognition, it is common
that the more training samples we use, the higher the recognition rate we get. So, the third …

… [21], investigated contactless palmprint recognition of newborn babies using a pre-trained
AlexNet. … On average, each palmprint has only 2.88 training samples in NTU-PI-v1 database, …

… training samples of diverse identities, which enables us to pretrain large-scale palmprint
recognition … , we propose to synthesize training data for palmprint recognition by manipulating …

… At each level, six images of each palmprint class are randomly chosen as training samples
to form the template and the remaining four images are used as testing samples. All of the …

… ) palmprint database (version 2), we compare the recognition … and limitations of current
palmprint recognition algorithms, we … Not all the training samples are used in our verification and …

… can learn higher-level features from massive training samples via a deep architecture, and it
… , we need to fine-tune the model trained for palmprint recognition. For this purpose, we used …