.png){kind=icon}
返回
Comparative study for 8 computational intelligence algorithms for human identification
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cosrev.2020.100237.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The biometric system includes the algorithms, procedures, and devices which are utilized for the purpose of recognizing individuals according to their behavioral and physiological features. The approaches of Computational Intelligence (CI) are utilized extensively to establish biometric-based identities as well as overcoming non-idealities usually exist in samples. The objective of this paper is to analyze and evaluate the various computational intelligence (CI) approaches for the human identification based on biometrics. The study includes 8 top CI algorithms, namely; k-Nearest Neighbor(K-NN), Artificial Neural Networks (ANNs), Support vector machines (SVMs), Fuzzy Discernibility Matrix (FDM), Naive Bayes (NB), k-means, Decision Trees (DTs), and Genetic algorithms (GAs). Also the study provides the technical characteristics and features of these algorithms as well as finds advantages and disadvantages of these methods. The analyzed algorithms can be selected according to quantity and quality of data presented at work. (c) 2020 Elsevier Inc. All rights reserved.
Keyword:
Biometrics
Intelligent algorithms
Computational intelligence
Human identification
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
12.7
论文数:
2.3K
被引数:
5.2K
机构
引用论文
Comparison of a logistic regression and Naive Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size滑坡敏感性评估中逻辑回归和朴素贝叶斯分类器的比较: 模型复杂性和训练数据集大小的影响.png)
CATENA
CATENAIF5.7
PREAI
分享收藏
分享收藏Predicting future hourly residential electrical consumption: A machine learning case study预测未来每小时住宅用电量: 机器学习案例研究ENERGY AND BUILDINGS
ENERGY AND BUILDINGSIF7.1
PREAI
分享收藏Neural network and multi-fractal dimension features for breast cancer classification from ultrasound images基于神经网络和多重分形特征的超声图像乳腺癌分类
PREAI
分享收藏
查看更多内容