Journal ArticleDOI
Towards contactless palmprint recognition
TLDR
A novel approach, namely CR_CompCode, which can achieve high recognition accuracy while having an extremely low computational complexity is proposed, which is highly effective and efficient for contactless palmprint identification.About:
This article is published in Pattern Recognition.The article was published on 2017-09-01. It has received 156 citations till now.read more
Citations
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Journal ArticleDOI
Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
Jing Zhang,Dacheng Tao +1 more
TL;DR: In this article, the authors present a comprehensive survey on AIoT to show how AI can empower the IoT to make it faster, smarter, greener, and safer, and highlight the challenges facing AI-oT and some potential research opportunities.
Posted Content
Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
Jing Zhang,Dacheng Tao +1 more
TL;DR: It is shown how AI can empower the IoT to make it faster, smarter, greener, and safer, and some promising applications of AIoT that are likely to profoundly reshape the authors' world are summarized.
Journal ArticleDOI
Feature Extraction Methods for Palmprint Recognition: A Survey and Evaluation
TL;DR: A unified framework is proposed to use a unified framework to classify palmprint images into four categories: 1) the contact-based; 2) contactless; 3) high-resolution; and 4) 3-D palm print images.
Journal ArticleDOI
PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition
TL;DR: PalmNet is a new method of applying Gabor filters in a CNN that uses a newly developed method to tune palmprint-specific filters through an unsupervised procedure based on Gabor responses and principal component analysis (PCA), not requiring class labels during training.
Journal ArticleDOI
Decade progress of palmprint recognition: A brief survey
TL;DR: A comprehensive overview of recent research progress of palmprint recognition as well as the basic background knowledge for it is presented, which mainly focuses on data acquisition, database, preprocessing, feature extraction, matching and fusion.
References
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Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: The Scale-Invariant Feature Transform (or SIFT) algorithm is a highly robust method to extract and consequently match distinctive invariant features from images that can then be used to reliably match objects in diering images.
Journal ArticleDOI
Robust Face Recognition via Sparse Representation
TL;DR: This work considers the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise, and proposes a general classification algorithm for (image-based) object recognition based on a sparse representation computed by C1-minimization.
Proceedings ArticleDOI
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
TL;DR: This work revisits both the alignment step and the representation step by employing explicit 3D face modeling in order to apply a piecewise affine transformation, and derive a face representation from a nine-layer deep neural network.
Book
Handbook of Fingerprint Recognition
TL;DR: This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.