Biometric Information Recognition Using Artificial Intelligence Algorithms: A Performance Comparison
نویسندگان
چکیده
Addressing crime detection, cyber security and multi-modal gaze estimation in biometric information recognition is challenging. Thus, trained artificial intelligence (AI) algorithms such as Support vector machine (SVM) adaptive neuro-fuzzy inference system (ANFIS) have been proposed to recognize distinct discriminant features of (intrinsic hand demographic cues) with good classification accuracy. Unfortunately, due nonlinearity information, accuracy SVM ANFIS reduced. As a result, optimized AI ((ANFIS) subtractive clustering (ANFIS-SC) error correction output code (SVM-ECOC)) shown be effective for recognition. In this paper, we compare the performance ANFIS-SC SVM-ECOC their effectiveness at learning essential characteristics intrinsic cues based on Pearson correlation coefficient (PCC) feature selection. Furthermore, these are presented, performances evaluated by root mean squared (RMSE), absolute percentage (MAPE), scatter index (SI), deviation (MAD), determination (R2), Akaike’s Information Criterion (AICc) Nash-Sutcliffe model efficiency (NSE). Evaluation results show that both suitable accurately recognizing soft basis measurements cues. Moreover, comparison demonstrated can provide better accuracy, RMSE, AICc, MAPE, R2 NSE values ≤ 3.85, 2.39E+02, 0.18%, ≥ 0.99 99, respectively.
منابع مشابه
Advances in Artificial Intelligence Using Speech Recognition
Abstract—This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily ro...
متن کاملArtificial Intelligence Tools in Health Information Management
Application of ICT in health (eHealth) has become an integral part of modern healthcare systems. Electronic health information management has proven useful in improving quality of health care, reducing costs and facilitating health research. However, the increasing complexity of healthcare and the growing demand for high quality healthcare delivery has created a need for eHealth systems with t...
متن کاملArtificial Intelligence Performance of linear - space search algorithms *
Search algorithms that use space linear in the search depth are widely employed in practice to solve difficult problems optimally, such as planning and scheduling. In this paper, we study the average-case performance of linear-space search algorithms, including depth-first branch-andbound (DFBnB), iterative-deepening (ID), and recursive best-first search (RBFS). To facilitate our analyses, we u...
متن کاملPerformance evaluation of artificial intelligence algorithms for virtual network embedding
Network virtualization is not only regarded as a promising technology to create an ecosystem for cloud computing applications, but also considered a promising technology for the future Internet. One of the most important issues in network virtualization is the virtual network embedding (VNE) problem, which deals with the embedding of virtual network (VN) requests in an underlying physical (subs...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3171850