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检索条件"任意字段=Proceedings of the 2017 International Conference on Biometrics Engineering and Application"

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Design and implementation of Marine biometrics identification and recommendation mini program based on YOLO 24

Design and implementation of Marine biometrics identificatio...

引用

8th international conference on Electronic Information Technology and Computer engineering, EITCE 2024

作者： Lin, Meirong Zheng, Zhiguo Wang, Hejia Zhang, Sijin Information Engineering College Hainan Vocational University of Science and Technology Hainan Haikou China School of Information and Communication Engineering Hainan University Haikou Hainan China

ISBN: (纸本)9798400710094

This paper presents a design and implementation scheme of Marine biometrics identification and recommendation mini program based on YOLO object detection algorithm. With the development and utilization of Marine resources, the demand for Marine biological identification and protection applications is increasing, so it is of great significance to design and implement an application that can intelligently identify Marine organisms and recommend high-quality seafood products. There are many limitations in the traditional Marine biometrics, such as fuzzy image and insufficient key technology of target detection. To solve these problems, the project team adopted the improved YOLO algorithm, combining a variety of techniques to improve the accuracy and real-time identification of Marine organisms. The Marine biological recognition and recommendation mini program based on YOLO algorithm can automatically identify the types of Marine organisms in the uploaded pictures, and provide relevant information and suggestions according to the identification results, helping users to understand the overview of Marine organisms more intuitively and clearly, and providing the recommendation function of nearby Marine product merchants. This project verifies the effectiveness and practicability of the mini program through practical application tests in different scenarios, providing the public with a convenient tool to enhance the understanding of Marine biodiversity and support the sustainable development of Marine ecosystems. © 2024 Copyright held by the owner/author(s).

关键词： biometrics

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Reviewing Facial Insight - A Smart Approach to Identity Unveiling Through Active Facial Patches and Multi-Task Cascaded Convolutional Networks 5

Reviewing Facial Insight - A Smart Approach to Identity Unve...

引用

5th international conference on Sustainable Communication Networks and application, ICSCNA 2024

作者： Kavin, F. Pradeepa, K. Selvalakshmi, B. Anitha, P. Subashini, K. Vijayalakshmi, P. Cyient Maharashtra Navi Mumbai India St. Michael College of Engineering & Technology Department of Computer Science and Engineering Tamil Nadu Sivaganga India Tagore Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Sri Sai Renganathan Engineering College Department of ECE Tamil Nadu Coimbatore India Tagore Engineering College Dept. of Information Technology Tamil Nadu Chennai India Knowledge Institute of Technology Department of Computer Science and Engineering Salem Tamil Nadu Chennai India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530013

This research work proposes an innovative method for enhancing facial recognition accuracy and efficiency by leveraging active facial patches and a Multi-Task Cascaded Convolutional Network (MTCNN). The review assesses the paper's contributions, methodology, experimental results, and potential impact on advancing facial recognition technology. It highlights the strengths of the proposed approach, including its clear problem statement, thorough methodology, compelling experimental results, and potential for real-world application. Additionally, the review offers recommendations for improvement, such as further exploration of potential biases and scalability considerations. Overall, Facial Insight presents a promising advancement in identity unveiling within facial recognition systems, contributing to the broader field of biometrics and computer vision. © 2024 IEEE.

关键词： biometrics

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Explainable AI in biometrics: A Novel Framework for Facial Recognition Interpretation

Explainable AI in Biometrics: A Novel Framework for Facial R...

引用

2024 IEEE international conference on Modeling, Simulation and Intelligent Computing, MoSICom 2024

作者： Agrawal, Ansh Kaur, Kirandeep Kaur, Harkeerat Indian Institute of Technology Computer Science Engineering Jammu & Kashmir Jammu India Indian Institute of Technology Faculty Computer Science Engineering Jammu & Kashmir Jammu India

ISBN: (纸本)9798331533311

In recent years, the integration of Explainable Artificial Intelligence (XAI) in facial biometrics has gained momentum, driven by a growing need for transparency in automated decision-making systems. This paper explores the application of XAI in face detection and identification to bridge the gap between model accuracy and interpretability, aiming to address challenges unique to biometric systems, including bias mitigation, user trust, and ethical implications. Unlike traditional 'black-box' models, the proposed framework incorporates visual and feature-based explanations that highlight key facial regions contributing to identification outcomes, enabling more transparent model assessments. We evaluate the effectiveness of state-of-the-art XAI techniques, such as SHAP, LIME, and Grad-CAM, through rigorous testing on diverse datasets under varying conditions, including occlusions, lighting, and facial expressions. Additionally, this research introduces a novel hybrid interpretability metric tailored to biometric applications, assessing the quality of explanations based on fidelity, usability, and impact on user trust. Results demonstrate that the proposed XAI-enhanced model offers insights into decision processes without compromising accuracy, advancing the state of explainability in biometric systems. This work underscores the importance of explainability as a means to achieve ethical, reliable, and legally compliant AI systems in sensitive domains like facial biometrics. © 2024 IEEE.

关键词： biometrics

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Fusion of Iris, Face, Fingerprint using Score Level Mechanism for Biometric application

Fusion of Iris, Face, Fingerprint using Score Level Mechanis...

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2023 IEEE international conference on Innovative Data Communication Technologies and application, ICIDCA 2023

作者： Balraj, E. Suryaprakash, M. Vignesh, P. Vigneshwar, R. Vinoth Kumar, A. M. Kumarasamy College of Engineering Department of Information Technology TamilNadu Karur India

ISBN: (纸本)9798350397208

When it comes to authentication, biometric systems evaluate unique characteristics about a person, such as their face, iris, or fingerprint. However, although this may seem like a greatsolution, multi-model biometrics may also lead to assaults like spoofing and limited accuracy. The capacity of multi-model biometrics technology to address challenges and fuel their development has recently drawn attention (Using VGG 16 and grassmann). With 92% accuracy, 1000 photos were classified into different categories using the proposed system's visual geometry group 16 for object identification and classification. In order to better organise and coordinate the images with the accounts, we may use the Grassmann manifoldlearning technique to finish the still to video planning strategy. The results of the experiment are quite convincing. © 2023 IEEE.

关键词： biometrics

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Deep Learning Approach for Ear Recognition and Longitudinal Evaluation in Children 23

Deep Learning Approach for Ear Recognition and Longitudinal ...

引用

23rd international conference of the biometrics Special Interest Group, BIOSIG 2024

作者： Hossain, Afzal Sultan, Tipu Chowdhury, Mohammad Zahir Uddin Schuckers, Stephanie Clarkson University Dept. of Electrical and Computer Engineering PotsdamNY United States Clarkson University Dept. of Mechanical and Aerospace Engineering PotsdamNY United States

ISBN: (纸本)9798350373714

Ear recognition as a biometric modality is becoming increasingly popular, with promising broader application areas. While current applications involve adults, one of the challenges in ear recognition for children is the rapid structural changes in the ear as they age. This work introduces a foundational longitudinal dataset collected from children aged 4 to 14 years over a 2.5-year period and evaluates ear recognition performance in this demographic. We present a deep learning based approach for ear recognition, using an ensemble of VGG16 and MobileNet, focusing on both adult and child datasets, with an emphasis on longitudinal evaluation for children. © 2024 IEEE.

关键词： Federated learning

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Biometric Hand Recognition by application of Particle Swarm Optimization Method 8

Biometric Hand Recognition by Application of Particle Swarm ...

引用

8th IEEE international conference on Image and Signal Processing and their applications, ISPA 2024

作者： Amar, Hichem Babes, Badreddine Hamouda, Noureddine Ghodbane, Hatem Amir, Monir Algiers Algeria University Mohamed Khider Biskra Algeria Mouloud Mammeri University Faculty of Electrical and Computer Engineering Department of Electronics Tizi-Ouzou Algeria

ISBN: (纸本)9798350309249

the field of biometrics research continues to advance, and although many identification and verification methods have been established, their effectiveness is still insufficient due to the increasing demands on security. For the purposes of biometric identification or authentication applications, hand biometric recognition has been effectively established. Multiple biometric methods are utilized since using only one biometric method often decreases the systems' confidence. In the present article, we suggest a multi-biometric fusion method for person recognition. In fact, we employ two different forms of biometrics: the hand's shape and palm print. The texture was extracted using discrete cosine transform (DCT) method. Subsequently, PSO algorithm is employed in the process of identification to integrate the geometric properties of the hands with the texture of the examined palm. Simulation results demonstrate the key benefits of this strategy with a realization rate of over 85% for a population of 230 people. © 2024 IEEE.

关键词： biometrics

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An Innovative application for Employee Attendance using Near Field Communication to Reduce the Time Complexity using IP and Geo Tracking Comparing with biometrics 2

An Innovative Application for Employee Attendance using Near...

引用

2nd IEEE international conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Shriraam, K. Deepa, N. Ezhil Grace, A. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai602105 India

ISBN: (纸本)9798350315905

A manually tracking thus every employee's attendance usually produces issues including precision and employee productivity. The current study focuses on the research to develop an IP and geo tracking-based attendance system software. This suggested effort seeks to lessen Time complexity of an employee attendance when compared to an existing system like biometrics. Materials and Methods: The study setup is in our University. Since it is an Attendance application Since there are no human samples involved, there is no ethical approval. The current study focuses on the research to design and develop a software of IP and Geo Tracking based attendance system. Accuracy of the Employee attendance application is performed with two groups: IP and Geo tracking, and biometrics of sample size (N=10), and G power is 80% threshold 0.05% , CI 95%. Results:- Its objective of the suggested article includes several characteristics and features of tracking employees, data management and monitoring and maintaining their records and providing information services. Independent sample T-Test was carried out using IP and Geo Tracking and biometrics. IP and Geo Tracking (81.25%) performs better than biometrics (79%). A statistically significant disparity exists between Geo Tracking and (p © 2023 IEEE.

关键词： Human resource management

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Sclera Vessel Analysis for Biometric System on Real Time Security application 2

Sclera Vessel Analysis for Biometric System on Real Time Sec...

引用

2nd IEEE international conference on Computer Vision and Machine Intelligence, CVMI 2023

作者： Anantharajan, Divya Saravanakumar, M. Bharathi Kannan, B. Ponmaniraj, S. Vandayar Engineering College Department of Computer Science and Engineering Thanjavur India Hindusthan College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Saveetha School of Engineering Simats Department of Computational Intelligence Thandalam India

ISBN: (纸本)9798350305142

biometrics has an unavoidable space in the era of security in terms of identifying the Individuals. There are many biometrics which are providing more prominent result, but all these biometrics needs the user cooperation in acquisition. The sclera, white portion of the eye, vessel patterns are holding the uniqueness to identify the individuals. This becomes the root of many researchers to recognize the individual with non-co-operative user images. Sclera recognitions are beginning of the new era which is to leads the recognition on the surveillance camera. Since the Image quality is less in the surveillance camera images and the segmentation of sclera is more challenging which has more impact on the accuracy of the recognition. To improve the accuracy of the segmentation Convolutional Neural Network has been used which has increase the time complexity of the system. Since the accuracy of the segmentation has increased and to optimize the time integro Differential Operator is utilized which reduces the searching area of the iris so the time taken will be reduced. The combination of CNN and DIO will increase the accuracy and complexity of the Segmentation Process. The experiments are carried out on the UBIRIS Dataset V2. © 2023 IEEE.

关键词： biometrics

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Mobile Educational application for Keystroke Dynamics Identification Systems 21

Mobile Educational Application for Keystroke Dynamics Identi...

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21st international conference on Emerging eLearning Technologies and applications, ICETA 2023

作者： Haluska, Renat Molcanyi, Dominik Pleva, Matus Hladek, Daniel Stas, Jan Su, Ming-Hsian Liao, Yuan-Fu Technical University of Košice Faculty of Electrical Engineering and Informatics Department of Electronics and Multimedia Communications Slovakia Soochow University Taiwan National Yang Ming Chiao Tung University Taiwan

ISBN: (纸本)9798350370690

This paper describes a chosen biometric method used in biometric systems to identify the user during online education interaction. The current demo page of the system is text-dependent, and it is planned to improve the identification and authentication mechanism to support continuous authentication and be able to detect cheating during online written exams. The article describes the keystroke dynamics method and informs the reader of current trends using this method and the implementation of keystroke dynamics within a web application used in an educational biometrics class. © 2023 IEEE.

关键词： biometrics

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Securing Biometric Data: Fully Homomorphic Encryption in Multimodal Iris and Face Recognition 23

Securing Biometric Data: Fully Homomorphic Encryption in Mul...

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23rd international conference of the biometrics Special Interest Group, BIOSIG 2024

作者： Singh, Surendra Igene, Lambert Schuckers, Stephanie Clarkson University Electrical and Computer Engineering New York United States

ISBN: (纸本)9798350373714

Multimodal biometric systems have gained popularity for their enhanced recognition accuracy and resistance to attacks like spoofing. This research explores methods for fusing iris and face feature vectors and implements robust security measures to protect fused databases and conduct matching operations on encrypted templates using fully homomorphic encryption (FHE). Evaluations on the QFIRE-I database demonstrate that our method effectively balances user privacy and accuracy while maintaining a high level of precision. Through experimentation, we demonstrate the effectiveness of employing FHE for template protection and matching within the encrypted domain, achieving notable results: a 96.41% True Acceptance Rate (TAR) for iris recognition, 81.19% TAR for face recognition, 98.81% TAR for iris fusion (left and right), and achieving a 100% TAR at 0.1% false acceptance rate (FAR) for face and iris fusion. The application of FHE presents a promising solution for ensuring accurate template matching while safeguarding user privacy and mitigating information leakage. © 2024 IEEE.

关键词： Face recognition

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