Face recognition using both visible light image and near-infrared image and a deep network-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Face recognition using both visible light image and near-infrared image and a deep network

Published:2017-03 Issue:1 Volume:2 Page:39-47
ISSN:2468-2322
Container-title:CAAI Transactions on Intelligence Technology
language:en
Short-container-title:CAAI Transactions on Intelligence Technology

Author:

Guo Kai,Wu Shuai,Xu Yong

Funder

Technology Innovation Project of Shenzhen

Shenzhen IOT

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Information Systems

Reference34 articles.

1. User identity verification via mouse dynamics;Feher;Inf. Sci.,2012

2. Feature extraction using a fast null space based linear discriminant analysis algorithms;Lu;Inf. Sci.,2012

3. Generating cancelable palmprint templates via coupled nonlinear dynamic filters and multiple orientation palmcodes;Li;Inf. Sci.,2010

4. Using the idea of the sparse representation to perform coarse-to-fine face recognition;Xu;Inf. Sci.,2013

5. ImageNet classification with deep convolutional neural networks;Krizhevsky;Adv. Neural Inf. Process. Syst.,2012

Cited by 68 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing face recognition performance: a comprehensive evaluation of deep learning models and a novel ensemble approach with hyperparameter tuning;Soft Computing;2024-08-13

2. Influence of multimodal training data for pipe segmentation in RGB and thermal infrared images in critical infrastructure;Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII;2024-06-07

3. A survey on disguise face recognition;Journal of the Chinese Institute of Engineers;2024-05-06

4. Enhanced Residual Network with Spatial and Channel Attention Mechanisms for Improved Face Recognition Performance;2024-04-29

5. Navigating the face recognition: unleashing the power of few-shot learning through metric-based insights;Multimedia Tools and Applications;2024-03-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3