Chaotic Krill Herd with Deep Transfer Learning-Based Biometric Iris Recognition System

作     者：Harbi Al-Mahafzah Tamer AbuKhalil Bassam A.Y.Alqaralleh 

作者机构：Department of Computer ScienceFaculty of Information TechnologyAl-Hussein Bin Talal University Ma’an71111Jordan MIS DepartmentCollege of Business AdministrationUniversity of Business and TechnologyJeddah21448Saudi Arabia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第73卷第12期

页      面：5703-5715页

核心收录：

学科分类：0502[文学-外国语言文学] 050201[文学-英语语言文学] 05[文学] 

主　　题：Biometric verification iris recognition deep learning parameter tuning machine learning 

摘      要：Biometric verification has become essential to authenticate the individuals in public and private *** several biometrics,iris has peculiar features and its working mechanism is complex in *** recent developments in Machine Learning and Deep Learning approaches enable the development of effective iris recognition *** this motivation,the current study introduces a novel Chaotic Krill Herd with Deep Transfer Learning Based Biometric Iris Recognition System(CKHDTL-BIRS).The presented CKHDTL-BIRS model intends to recognize and classify iris images as a part of biometric *** achieve this,CKHDTL-BIRS model initially performs Median Filtering(MF)-based preprocessing and segmentation for iris *** addition,MobileNetmodel is also utilized to generate a set of useful feature ***,Stacked Sparse Autoencoder(SSAE)approach is applied for *** last,CKH algorithm is exploited for optimization of the parameters involved in SSAE *** proposed CKHDTL-BIRS model was experimentally validated using benchmark dataset and the outcomes were examined under several *** comparison study results established the enhanced performance of CKHDTL-BIRS technique over recent approaches.