Relevant bibliographies by topics / Fingerprint Module

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fingerprint Module'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Fingerprint Module"

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Zhu, Zhiren. "The Electronic Lock of Fingerprint Identification." Frontiers in Computing and Intelligent Systems 5, no. 3 (2023): 65–68. http://dx.doi.org/10.54097/fcis.v5i3.13857.

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Biometrics is more and more widely used in the security system, with the current realistic needs as a starting point, a microcontroller-based fingerprint identification electronic lock design method is proposed to realize the transformation from the traditional security system door locks to the new fingerprint identification electronic locks. This design uses the matrix keyboard to enter the password and fingerprint to unlock the door in two ways: Through the fingerprint module to collect fingerprints; stm32 microcontroller as the main control module of the fingerprint identification electroni
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Fatema, A. Shaikh*, and Prof.S.O.Rajankar. "BIOMETRIC AUTHENTICATION SYSTEM USING RPI." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 4 (2016): 839–44. https://doi.org/10.5281/zenodo.50420.

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A biometric authentication system acquires biometric sample such as fingerprint. The fingerprint signifies physiological features of an individual.This is a system which maintains the attendance records of students automatically. In this  designing of an efficient module that comprises of a fingerprint sensor to manage the attendance records of students. This module enrolls the student’s as well as staff’s fingerprints. This enrolling is a onetime process and their fingerprints will be stored in the fingerprint sensor. During enrolling of fingerprints alone requires a system s
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Nguyen, Thi, Eunsoo Park, Xuenan Cui, Van Nguyen, and Hakil Kim. "fPADnet: Small and Efficient Convolutional Neural Network for Presentation Attack Detection." Sensors 18, no. 8 (2018): 2532. http://dx.doi.org/10.3390/s18082532.

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The rapid growth of fingerprint authentication-based applications makes presentation attack detection, which is the detection of fake fingerprints, become a crucial problem. There have been numerous attempts to deal with this problem; however, the existing algorithms have a significant trade-off between accuracy and computational complexity. This paper proposes a presentation attack detection method using Convolutional Neural Networks (CNN), named fPADnet (fingerprint Presentation Attack Detection network), which consists of Fire and Gram-K modules. Fire modules of fPADnet are designed followi
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Yeniwati, Desy, Riswan, Nilawati, and Trigina. "SISTEM ABSENSI SISWA MENGGUNAKAN FINGERPRINT BERBASIS ARDUINO MEGA 2560." FORTECH (Journal of Information Technology) 6, no. 1 (2022): 26–31. http://dx.doi.org/10.53564/fortech.v6i1.874.

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This study aims to design, create and test the attendance system of SMA Dharma Bhakti 4 Jambi City students using Arduino Mega 2560-based Fingerprint. This research was conducted at SMA Dharma Bhakti 4 Jambi City from January to April 2021.This research was conducted using the R and D (Research and Development) method which includes planning, designing, manufacturing and testing tools carried out by making a tool system with input in the form of a Fingerprint Module. Control system with Arduino Mega 2560. Output system in the form of LCD and SMS reports to parents of SMA Dharma Bhakti 4 studen
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S, Kanagamalliga, Rajalingam S, Kannan A, and Karthikeyan M. "Biometric and IoT Integration for Secure and Remote Door Access Control Using Fingerprint Recognition and GSM Technology." E3S Web of Conferences 619 (2025): 03013. https://doi.org/10.1051/e3sconf/202561903013.

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The research focuses on improving the security and convenience of door access control systems through the integration of advanced fingerprint recognition technology with Arduino microcontrollers and the GSM module. The reliability and flexibility of Arduino, coupled with the GSM capabilities of SIM900, are utilized to create a robust and efficient solution. Fingerprints are captured and verified using a fingerprint sensor, ensuring precise and personalized access control. The Arduino board acts as the main controller, processing fingerprint data and enabling communication with the GSM module f
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Marák, Pavol, and Alexander Hambalík. "Fingerprint Recognition System Using Artificial Neural Network as Feature Extractor: Design and Performance Evaluation." Tatra Mountains Mathematical Publications 67, no. 1 (2016): 117–34. http://dx.doi.org/10.1515/tmmp-2016-0035.

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Abstract Performance of modern automated fingerprint recognition systems is heavily influenced by accuracy of their feature extraction algorithm. Nowadays, there are more approaches to fingerprint feature extraction with acceptable results. Problems start to arise in low quality conditions where majority of the traditional methods based on analyzing texture of fingerprint cannot tackle this problem so effectively as artificial neural networks. Many papers have demonstrated uses of neural networks in fingerprint recognition, but there is a little work on using them as Level-2 feature extractors
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Rinchai, Darawan, Jessica Roelands, Mohammed Toufiq, et al. "BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R." Bioinformatics 37, no. 16 (2021): 2382–89. http://dx.doi.org/10.1093/bioinformatics/btab121.

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Abstract Motivation We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. Results We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performe
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Sun, Yuting, Yanfeng Tang, and Xiaojuan Chen. "A Neural Network-Based Partial Fingerprint Image Identification Method for Crime Scenes." Applied Sciences 13, no. 2 (2023): 1188. http://dx.doi.org/10.3390/app13021188.

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Fingerprints are the most widely used of all biological characteristics in public safety and forensic identification. However, fingerprint images extracted from the crime scene are incomplete. On the one hand, due to the lack of effective area in partial fingerprint images, the extracted features are insufficient. On the other hand, a broken ridge may lead to a large number of false feature points, which affect the accuracy of fingerprint recognition. Existing fingerprint identification methods are not ideal for partial fingerprint identification. To overcome these problems, this paper propose
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Jiang, Yujia, and Xin Liu. "Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid." Journal of Electrical and Computer Engineering 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/1539298.

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Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP) in spatial pyramid is applied to recognize fingerprint livene
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Lao, Fei, and Guo Xin Li. "The Design of Storage Box Control System Based on Fingerprint Identification." Applied Mechanics and Materials 727-728 (January 2015): 778–80. http://dx.doi.org/10.4028/www.scientific.net/amm.727-728.778.

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For the design of storagebox control system supplied to fixed customers , this paper presents the designideas that the storage box controlsystem based on fingerprint identification.The core design philosophy is basedon the PC as the core, connecting the fingerprint recognition module and thepower locks array control systems through two com ports. through the smalldatabase system on the PC, it can manage the two moduls effectively.When theuser's fingerprint match, the fingerprint identification module returns to thePC a finger signal,the small datebase will correct the electricity lock of theus
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Dissertations / Theses on the topic "Fingerprint Module"

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MacNair, David Luke. "Modeling cellular actuator arrays." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50259.

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This work explores the representations and mathematical modeling of biologically-inspired robotic muscles called Cellular Actuator Arrays. These actuator arrays are made of many small interconnected actuation units which work together to provide force, displacement, robustness and other properties beyond the original actuator's capability. The arrays can also exhibit properties generally associated with biological muscle and can thus provide test bed for research into the interrelated nature of the nervous system and muscles, kinematics/dynamics experiments to understand balance and synergie
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Doria, Felipe França. "Padrões estruturados e campo aleatório em redes complexas." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/144076.

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Este trabalho foca no estudo de duas redes complexas. A primeira é um modelo de Ising com campo aleatório. Este modelo segue uma distribuição de campo gaussiana e bimodal. Uma técnica de conectividade finita foi utilizada para resolvê-lo. Assim como um método de Monte Carlo foi aplicado para verificar os resultados. Há uma indicação em nossos resultados que para a distribuição gaussiana a transição de fase é sempre de segunda ordem. Para as distribuições bimodais há um ponto tricrítico, dependente do valor da conectividade . Abaixo de um certo mínimo de , só existe transição de segunda ordem.
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Man-Wu, Shou, and 吳守滿. "Bending and laminating module design for Fingerprint Identification components." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/a3hp6n.

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碩士<br>中原大學<br>機械工程研究所<br>105<br>Abstract A micro-wound element is designed for the bending and fitting module of the finge rprint identification. The ultrasonic fingerprint identification component is different from the general fingerprint identification since the launch units in front of FPC need to be attached to the other side of the TFT. Automatic alignment is more difficult than the composite chip of multi-layer component. The bonding circuit conduction of the soft cable between the FPC and the TFT combines them. After the completion of position identification, the position compensatio
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Wu, Yung-Yu, and 吳永裕. "Study of Embedded Fingerprint Identification Module in Electro-Mechanical Lock." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/92782169498142805150.

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碩士<br>淡江大學<br>機械與機電工程學系碩士班<br>96<br>The objective of this thesis is to develop a fingerprint identification module embedded on a traditional electro-mechanical lock. It becomes a new security product(bio-lock) with dual functions. The embedded security products are more and more popular now a day. So, it becomes more important to develop an embedded product for the secure purposes. From the practical point of view, the fingerprint is one of the mature techniques in security industry. It needs to consider the cost, functions, product volume size, security label and operator convenience for m
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Lin, Wei-Cheng, and 林洧鋮. "Design and Implementation of High Speed Fingerprint Module on ARM Platform." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/07436077736576905026.

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碩士<br>國立清華大學<br>電機工程學系<br>101<br>The fingerprint recognition is the most widely used biometric recognition technology nowadays. International Organization for Standardization (ISO) had established and announced the standard format for the fingerprint template (ISO19794-2) since 2005.The minutiae is defined as ridge ending and ridge bifurcation, and minutiae information contains coordinate, direction and type. The matching speed under large scale fingerprint database is a challenge of fingerprint identification application. The minutia-based fingerprint matching method takes more matching time
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Eadara, Archana. "Modeling, analysis, and simulation of Muzima fingerprint module based on ordinary and time Petri nets." Thesis, 2016. http://hdl.handle.net/1805/10800.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>In the healthcare industry, several modern patient identification and patient matching systems have been introduced. Most of these implement patient identification by their first, middle and last names. They also use Social Security Number and other similar national identifiers. These methods may not work for many developing and underdeveloped countries where identifying a patient is a challenge with highly redundant and interchangeable first and last names of the patient, this is aggravated by the absence of a national identificati
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Books on the topic "Fingerprint Module"

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Sparrow, Malcolm K. A topological approach to the matching of single fingerprints: Development of algorithms for use on latent fingermarks. National Bureau of Standards, 1985.

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Sparrow, Malcolm K. A topological approach to the matching of single fingerprints: Development of algorithms for use on rolled impressions. U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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Sparrow, Malcolm K. A topological approach to the matching of single fingerprints: Development of algorithms for use on latent fingermarks. U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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Sparrow, Malcolm K. A topological approach to the matching of single fingerprints: Development of algorithms for use on latent fingermarks. U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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Book chapters on the topic "Fingerprint Module"

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Lim, Sung Jin, Seung-Hoon Chae, Deasung Moon, Yongwha Chung, Namil Lee, and Sung Bum Pan. "VLSI Architecture for the Fuzzy Fingerprint Vault with Automatic Alignment Module." In Communication and Networking. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10844-0_54.

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Vinotheni, M. S., A. Rajasekar, M. Shabana Parveen, J. Bino, N. Vidhya, and Parameswaran Ramesh. "Fingerprint-based security system for mitigating voting corruption." In Security Issues in Communication Devices, Networks and Computing Models. CRC Press, 2025. https://doi.org/10.1201/9781003513445-9.

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Kang, Hyosup, Bongku Lee, Hakil Kim, Daecheol Shin, and Jaesung Kim. "A Study on Performance Evaluation of the Liveness Detection for Various Fingerprint Sensor Modules." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45226-3_169.

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Nascimben, Mauro, Silvia Spriano, Lia Rimondini, and Manolo Venturin. "Molecular Fingerprint Based and Machine Learning Driven QSAR for Bioconcentration Pathways Determination." In Mathematical Models and Computer Simulations for Biomedical Applications. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35715-2_7.

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Stahlke, Maximilian, Tobias Feigl, Sebastian Kram, Jonathan Ott, Jochen Seitz, and Christopher Mutschler. "Data-driven Wireless Positioning." In Unlocking Artificial Intelligence. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64832-8_10.

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AbstractRadio-based indoor localization is a crucial enabler for various tasks like robot navigation or quality assurance in industrial assembly. However, especially industrial environments often present challenging propagation conditions, with reflections, diffraction obstruction, and blockage. While traditional, lateration-based positioning algorithms can provide high accuracies in line-of-sight (LOS) conditions, signal blockages cause non-line-of-sight (NLOS) propagation and degrade the performance dramatically. To overcome this problems, recently artificial intelligence (AI)-driven localiz
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Marcialis, Gian Luca, Fabio Roli, Pietro Coli, and Giovanni Delogu. "A Fingerprint Forensic Tool for Criminal Investigations." In Handbook of Research on Computational Forensics, Digital Crime, and Investigation. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-836-9.ch002.

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In this chapter, the authors describe the software module developed in the context of a joint research work between the Department of Electrical and Electronic Engineering of the University of Cagliari, and Raggruppamento Carabinieri Investigazioni Scientifiche (Scientific Investigation Office) of the “Arma dei Carabinieri”, that is the militia maintained by the Italian government for police duties. Aim of the joint research work has been the study of state of the art on methods and algorithms for automatic analysis of latent fingerprint images and for fake fingerprints identification. The res
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Lennard, Chris. "Forensic Sciences: Fingerprint Techniques." In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier, 2018. http://dx.doi.org/10.1016/b978-0-12-409547-2.00190-6.

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Conti V., Militello C., Sorbello F., and Vitabile S. "An Embedded Fingerprints Classification System based on Weightless Neural Networks." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2009. https://doi.org/10.3233/978-1-58603-984-4-67.

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Automatic fingerprint classification provides an important indexing scheme to facilitate efficient matching in large-scale fingerprint databases in Automatic Fingerprint Identification Systems (AFISs). The paper presents a new fast fingerprint classification module implementing on embedded Weightless Neural Network (RAM-based neural network). The proposed WNN architecture uses directional maps to classify fingerprint images in the five NIST classes (Left Loop, Right Loop, Whorl, Arch and Tented Arch) without anyone enhancement phase. Starting from the directional map, the WNN architecture comp
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Agatonovic-Kustrin, Snezana, and David W. Morton. "Thin-Layer Chromatography: Fingerprint Analysis of Plant Materials." In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier, 2017. http://dx.doi.org/10.1016/b978-0-12-409547-2.14024-7.

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Baral, Prashant, Ning Yang, and Ning Weng. "IoT Device Identification Using Device Fingerprint and Deep Learning." In Deep Learning and Reinforcement Learning [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.111554.

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The foundation of security in IoT devices lies in their identity. However, traditional identification parameters, such as MAC address, IP address, and IMEI, are vulnerable to sniffing and spoofing attacks. To address this issue, this paper proposes a novel approach using device fingerprinting and deep learning for device identification. Device fingerprinting is generated by analyzing inter-arrival time (IAT), round trip time (RTT), or IAT/RTT outliers of packets used for communication in networks. We trained deep learning models, namely convolutional neural network (CNN) and CNN + LSTM (long s
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Conference papers on the topic "Fingerprint Module"

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Song, Hae Jin, Mahyar Khayatkhoei, and Wael AbdAlmageed. "ManiFPT: Defining and Analyzing Fingerprints of Generative Models." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01026.

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Ribeiro, Rui, Joao P. Carvalho, and Luisa Coheur. "Leveraging Fuzzy Fingerprints from Large Language Models for Authorship Attribution." In 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2024. http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10612177.

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Zhang, Longqing, Kei Chang, Jinwen He, et al. "Voiceprint Unlocking Based on MFCC—Exploration of Voiceprint Models Different from Fingerprint." In 2024 IEEE 2nd International Conference on Image Processing and Computer Applications (ICIPCA). IEEE, 2024. http://dx.doi.org/10.1109/icipca61593.2024.10709042.

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Joseph, Jerome, Shaun Mathew Crasta, Samson Eioan Dsouza, Eadoin Lobo, Shrisha H. S, and Sofia Rego. "Predicting Bioactivity Using Chemical Fingerprint Models & Cell Morphology with Deep Neural Networks." In 2024 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER). IEEE, 2024. http://dx.doi.org/10.1109/discover62353.2024.10750662.

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Kadhim, Saif Mohanad, Johnny Koh Siaw Paw, Yaw Chong Tak, and Shahad Thamear Abd Al-Latief. "Instant Fingerprint Recognition Using Optimized Machine Learning Models by Corona Virus Optimization Algorithm." In 2024 International Conference on Intelligent Computing and Next Generation Networks (ICNGN). IEEE, 2024. https://doi.org/10.1109/icngn63705.2024.10871538.

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Bin Mohamed Ghazali, Mohamed Aizad, Aroland Kiring, Lyudmila Mihaylova, Hoe Tung Yew, Seng Kheau Chung, and Yan Yan Farm. "Evaluation of Theoretical and Empirical Log-Normal Models for Wi-Fi Fingerprint Mapping in Indoor Positioning." In 2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET). IEEE, 2024. http://dx.doi.org/10.1109/iicaiet62352.2024.10730353.

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Wongsekleo, Prab, Lapat Nakpaen, Panarat Cherntanomwong, and Charnon Pattiyanon. "Time Reduction for Collecting Fingerprint Data in Indoor Positioning Systems with Generated Synthetic Data by Ensemble Models and GANs." In 2024 19th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). IEEE, 2024. https://doi.org/10.1109/isai-nlp64410.2024.10799319.

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Taylor, Christopher, Leslie Bland, Gerald Frankel, et al. "Predicting Corrosion Fatigue Behavior Using a Bayesian Network That Integrates Microstructure, Electrochemistry and Fracture Mechanics." In CORROSION 2018. NACE International, 2018. https://doi.org/10.5006/c2018-11228.

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Abstract The localized corrosion and cracking of lightweight alloys is a complex, non-linear and stochastic function of the variables concerning materials composition, thermal and mechanical processing, and environmental parameters such as solution chemistry, temperature, electrochemical potential and mechanical stress. Integrating these variables into a coherent model poses a ‘grand challenge’ in corrosion science and engineering. In this conference paper, a Bayesian network approach that integrates these variables into a single model is presented based upon pre-existing models taken from the
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Wenzl, Matthias, and Daniel Kluka. "Adding Channel Security to a Fingerprint Verification Chain." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67356.

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Authenticating persons using fingerprints is a widely accepted method in the field of access control, border control, prosecution and many others. Today, fingerprint modules with customizable firmware can be bought commercially off the shelf by hobbyists and small companies to be used in their applications and are usually locally separated from a controller implementing the feature extraction and comparison algorithms. As a matter of fact, the communication channel between the sensor and the controller module is susceptible to eavesdropping and man in the middle attacks. Nevertheless, adding c
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Feng Lei, Zhang Xin, Liang Chunhui, and Li Tianyu. "Research of fingerprint module detector system." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5619030.

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Reports on the topic "Fingerprint Module"

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Perdigão, Rui A. P. Information physics and quantum space technologies for natural hazard sensing, modelling and prediction. Meteoceanics, 2021. http://dx.doi.org/10.46337/210930.

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Disruptive socio-natural transformations and climatic change, where system invariants and symmetries break down, defy the traditional complexity paradigms such as machine learning and artificial intelligence. In order to overcome this, we introduced non-ergodic Information Physics, bringing physical meaning to inferential metrics, and a coevolving flexibility to the metrics of information transfer, resulting in new methods for causal discovery and attribution. With this in hand, we develop novel dynamic models and analysis algorithms natively built for quantum information technological platfor
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Irudayaraj, Joseph, Ze'ev Schmilovitch, Amos Mizrach, Giora Kritzman, and Chitrita DebRoy. Rapid detection of food borne pathogens and non-pathogens in fresh produce using FT-IRS and raman spectroscopy. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7587221.bard.

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Rapid detection of pathogens and hazardous elements in fresh fruits and vegetables after harvest requires the use of advanced sensor technology at each step in the farm-to-consumer or farm-to-processing sequence. Fourier-transform infrared (FTIR) spectroscopy and the complementary Raman spectroscopy, an advanced optical technique based on light scattering will be investigated for rapid and on-site assessment of produce safety. Paving the way toward the development of this innovative methodology, specific original objectives were to (1) identify and distinguish different serotypes of Escherichi
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Calafat, Francisco Mir, Thomas Frederikse, and Kevin Horsburgh. Mediterranean trend and acceleration sea-level estimates. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d5.2_v2.

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Sea-level change is geographically non-uniform, with regional departures that can reach several times the global average rate of change. Characterizing this spatial variability and understanding its causes is crucial to the design of adaptation strategies for sea-level rise. This, as it turns out, is no easy feat, primarily due to the sparseness of the observational sea-level record in time and space. Long tide gauge records are restricted to a few locations along the coast. Satellite altimetry offers a better spatial coverage but only since 1992. In the Mediterranean Sea, the tide gauge netwo
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Yogev, David, Ricardo Rosenbusch, Sharon Levisohn, and Eitan Rapoport. Molecular Pathogenesis of Mycoplasma bovis and Mycoplasma agalactiae and its Application in Diagnosis and Control. United States Department of Agriculture, 2000. http://dx.doi.org/10.32747/2000.7573073.bard.

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Mycoplasma bovis and M. agalactiae are two phylogenetically related mycoplasmas which cause economically significant diseases in their respective bovine or small ruminant hosts. These organisms cause persistent asymptomatic infections that can result in severe outbreaks upon introduction of carrier animals into susceptible herds. Little is known about the mechanisms underlying mycoplasma-host interaction, variation in virulence, or of the factors enabling avoidance of the host immune system. In recent years it has become apparent that the ability of pathogenic microorganisms to rapidly alter s
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