Relevant bibliographies by topics / Software based face antispoofing techniques

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Academic literature on the topic 'Software based face antispoofing techniques'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Software based face antispoofing techniques"

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Vinutha, H., and G. Thippeswamy. "Antispoofing in face biometrics: a comprehensive study on software-based techniques." Computer Science and Information Technologies 4, no. 1 (2023): 1–13. https://doi.org/10.11591/csit.v4i1.pp1-13.

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The vulnerability of the face recognition system to spoofing attacks has piqued the biometric community's interest, motivating them to develop antispoofing techniques to secure it. Photo, video, or mask attacks can compromise face biometric systems (types of presentation attacks). Spoofing attacks are detected using liveness detection techniques, which determine whether the facial image presented at a biometric system is a live face or a fake version of it. We discuss the classification of face anti-spoofing techniques in this paper. Anti-spoofing techniques are divided into two categories
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H, Vinutha, and Thippeswamy G. "Antispoofing in face biometrics: a comprehensive study on software-based techniques." Computer Science and Information Technologies 4, no. 1 (2023): 1–13. http://dx.doi.org/10.11591/csit.v4i1.p1-13.

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The vulnerability of the face recognition system to spoofing attacks has piqued the biometric community's interest, motivating them to develop anti-spoofing techniques to secure it. Photo, video, or mask attacks can compromise face biometric systems (types of presentation attacks). Spoofing attacks are detected using liveness detection techniques, which determine whether the facial image presented at a biometric system is a live face or a fake version of it. We discuss the classification of face anti-spoofing techniques in this paper. Anti-spoofing techniques are divided into two categories: h
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H, Vinutha, and Thippeswamy G. "Antispoofing in face biometrics: a comprehensive study on software-based techniques." Computer Science and Information Technologies 4, no. 1 (2023): 1–13. http://dx.doi.org/10.11591/csit.v4i1.pp1-13.

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The vulnerability of the face recognition system to spoofing attacks has piqued the biometric community's interest, motivating them to develop antispoofing techniques to secure it. Photo, video, or mask attacks can compromise face biometric systems (types of presentation attacks). Spoofing attacks are detected using liveness detection techniques, which determine whether the facial image presented at a biometric system is a live face or a fake version of it. We discuss the classification of face anti-spoofing techniques in this paper. Anti-spoofing techniques are divided into two categories: ha
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V. Chakole, Vijay, and Swati R. Dixit. "MLbFA." International journal of electrical and computer engineering systems 16, no. 4 (2025): 321–32. https://doi.org/10.32985/ijeces.16.4.5.

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The primary aim of the research paper is to deploy an efficient automated face antispoofing system that could consider replay attacks in the presence of partial occlusions. For this purpose, the article introduces a novel machine learning-based face- antispoofing (MLbFA) framework. The system incorporates a modified version of the difference of the Gaussian technique to compute the overall contrast of the input images which is later used to enhance the contrast of the image using contrast correction. On the other hand, the image details, especially the edges are enhanced for significant featur
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Ren, Hanchi, Yi Hu, San Hlaing Myint, et al. "A Real-Time and Long-Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT-Based Multimedia Communication Systems." Wireless Communications and Mobile Computing 2021 (October 31, 2021): 1–15. http://dx.doi.org/10.1155/2021/6711561.

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The development of the Internet of Things (IoT) stimulates many research works related to Multimedia Communication Systems (MCS), such as human face detection and tracking. This trend drives numerous progressive methods. Among these methods, the deep learning-based methods can spot face patch in an image effectively and accurately. Many people consider face tracking as face detection, but they are two different techniques. Face detection focuses on a single image, whose shortcoming is obvious, such as unstable and unsmooth face position when adopted on a sequence of continuous images; computin
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Shivani, Dugyala. "Attention-Oriented Two-Stream Convolutional Networks for the Identification of Face Spoofing." International Journal for Research in Applied Science and Engineering Technology 12, no. 12 (2024): 176–81. https://doi.org/10.22214/ijraset.2024.65732.

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Face recognition has been extensively researched and has seen tremendous success in a variety of applications over the past few decades because the human face retains the most information for identifying individuals. Modern face recognition systems are still vulnerable to face spoofing attacks, such as the face video replay attack. Despite the fact that numerous efficient antispoofing techniques have been put forth, we discover that illuminations impair the effectiveness of many of the current techniques. It encourages us to create illumination-invariant anti-spoofing techniques. In this work,
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Akhtar, Zahid, and Gian Luca Foresti. "Face Spoof Attack Recognition Using Discriminative Image Patches." Journal of Electrical and Computer Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/4721849.

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Face recognition systems are now being used in many applications such as border crossings, banks, and mobile payments. The wide scale deployment of facial recognition systems has attracted intensive attention to the reliability of face biometrics against spoof attacks, where a photo, a video, or a 3D mask of a genuine user’s face can be used to gain illegitimate access to facilities or services. Though several face antispoofing or liveness detection methods (which determine at the time of capture whether a face is live or spoof) have been proposed, the issue is still unsolved due to difficulty
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Kadar, Rozita, Jamal Othman, and Naemah Abdul Wahab. "Survey on Ontology-Based Visualization Techniques towards Program Comprehension Application." Journal of Computing Research and Innovation 3, no. 1 (2018): 19–29. http://dx.doi.org/10.24191/jcrinn.v3i1.66.

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A key challenge to software maintainers during performing the software maintenance is to comprehend a source code. Source code plays an important role in aiding software maintainers to get conversant with a software system since some system documentations are often unavailable or outdated. Although there are many researches that have discussed the different strategies and techniques to overcome the program comprehension problem, there exists only a shallow knowledge about the challenges software maintainers face when trying to understand a software system through reading source code. In order
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Deshmukh, Amar B., and N. Usha Rani. "Optimization-Driven Kernel and Deep Convolutional Neural Network for Multi-View Face Video Super Resolution." International Journal of Digital Crime and Forensics 12, no. 3 (2020): 77–95. http://dx.doi.org/10.4018/ijdcf.2020070106.

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One of the major challenges faced by video surveillance is recognition from low-resolution videos or person identification. Image enhancement methods play a significant role in enhancing the resolution of the video. This article introduces a technique for face super resolution based on a deep convolutional neural network (Deep CNN). At first, the video frames are extracted from the input video and the face detection is performed using the Viola-Jones algorithm. The detected face image and the scaling factors are fed into the Fractional-Grey Wolf Optimizer (FGWO)-based kernel weighted regressio
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Peng, Peng, Ivens Portugal, Paulo Alencar, and Donald Cowan. "A face recognition software framework based on principal component analysis." PLOS ONE 16, no. 7 (2021): e0254965. http://dx.doi.org/10.1371/journal.pone.0254965.

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Face recognition, as one of the major biometrics identification methods, has been applied in different fields involving economics, military, e-commerce, and security. Its touchless identification process and non-compulsory rule to users are irreplaceable by other approaches, such as iris recognition or fingerprint recognition. Among all face recognition techniques, principal component analysis (PCA), proposed in the earliest stage, still attracts researchers because of its property of reducing data dimensionality without losing important information. Nevertheless, establishing a PCA-based face
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Book chapters on the topic "Software based face antispoofing techniques"

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Bernier, Téo, Yani Ziani, Nikolai Kosmatov, and Frédéric Loulergue. "Combining Deductive Verification with Shape Analysis." In Fundamental Approaches to Software Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57259-3_14.

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AbstractDeductive verification tools can prove a large range of program properties, but often face issues on recursive data structures. Abstract interpretation tools based on separation logic and shape analysis can efficiently reason about such structures but cannot deal with so large classes of properties. This short paper presents an ongoing work on combining both techniques. We show how a deductive verifier for C programs, Frama-C/Wp, can benefit from a shape analysis tool, MemCAD, where structural and separation properties proved in the latter become assumptions for the former. A case stud
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Beyer, Dirk, Thomas Lemberger, and Henrik Wachowitz. "CPA-Daemon: Mitigating Tool Restarts for Java-Based Verifiers." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78750-8_8.

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Abstract We present CPA-Daemon, a microservice for continuous software verification of C code. CPA-Daemon provides full access to the verifier CPAchecker, but adds a clear network interface based on gRPC that abstracts from three different modes of execution: (1) running CPAchecker in a separate JVM, (2) running CPAchecker as a native executable compiled with GraalVM, and (3) running CPAchecker in a shared, continuously-running JVM. The last two are novel execution modes that greatly improve the response time of verification in different verification scenarios and enable the seamless integrati
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Sanderson, David, Emma Shires, Jack C. Chaplin, Harvey Brookes, Amer Liaqat, and Svetan Ratchev. "Context-Aware Plug and Produce for Robotic Aerospace Assembly." In IFIP Advances in Information and Communication Technology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72632-4_13.

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AbstractAerospace production systems face increasing requirements for flexibility and reconfiguration, along with considerations of cost, utilisation, and efficiency. This drives a need for systems with a small number of automation platforms (e.g. industrial robots) that can make use of a larger number of end effectors that are potentially flexible or multifunctional. This leads to the challenge of ensuring that the configuration and location of each end effector is tracked by the system at all times, even in the face of manual adjustments, to ensure that the correct processes are applied to t
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Lu, Junyi, Xiaojia Li, Zihan Hua, et al. "DeepCRCEval: Revisiting the Evaluation of Code Review Comment Generation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-90900-9_3.

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Abstract Code review is a vital but demanding aspect of software development, generating significant interest in automating review comments. Traditional evaluation methods for these comments, primarily based on text similarity, face two major challenges: inconsistent reliability of human-authored comments in open-source projects and the weak correlation of text similarity with objectives like enhancing code quality and detecting defects. This study empirically analyzes benchmark comments using a novel set of criteria informed by prior research and developer interviews. We then similarly revisi
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Sanchez-Moreno, Alejandra Sarahi, Hector Manuel Perez-Meana, Jesus Olivares-Mercado, Gabriel Sanchez-Perez, and Karina Toscano-Medina. "Comparison of Face Detection and Recognition Algorithms in Real-Time Video." In Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques. IOS Press, 2020. http://dx.doi.org/10.3233/faia200567.

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Facial recognition systems has captivated research attention in recent years. Facial recognition technology is often required in real-time systems. With the rapid development, diverse algorithms of machine learning for detection and facial recognition have been proposed to address the challenges existing. In the present paper we proposed a system for facial detection and recognition under unconstrained conditions in video sequences. We analyze learning based and hand-crafted feature extraction approaches that have demonstrated high performance in task of facial recognition. In the proposed sys
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Madhusudan, D., and Prudhvi Raj Budumuru. "FACE RECOGNITION WITH VOICE APPLICATION." In Artificial Intelligence and Emerging Technologies. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/nbennurch306.

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Facial recognition may be a biometric identification method that is non-intraoperative and suited for many different kinds of applications. It is necessary for implementing the method with a considerable while and appropriate precision while taking hardware timing into account. The application of a machine learning method for instant facial picture recognition is the main focus of this study. The face recognition software employs algorithms to virtually confirm a person's identification by comparing a digital image taken with a camera to a face print that has been stored. One of the key facial
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Renna, Paolo. "Learning Methodologies to Support E-Business in the Automated Negotiation Process." In Intelligent Technologies and Techniques for Pervasive Computing. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-4038-2.ch003.

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The automated negotiation performed by a software agent is investigated in order to improve the benefits compared to a humane face-to-face negotiation. The profitability of e-business applications can be increased by the support of automated negotiation tools. This research proposes a set of learning methodologies to support both the suppliers’ and customers’ negotiation activities. The learning methodologies are based on Q-learning technique, which is able to evaluate the utility of the actions without a model of the environment. The context regards one-to-many negotiation and multi-issues (v
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Juneja, Sonia. "Efficient Software Cost Estimation Using Artificial Intelligence." In Advances in Systems Analysis, Software Engineering, and High Performance Computing. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3502-4.ch009.

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Accurate cost estimation is desired for efficient budget planning and monitoring. Traditional approach for software cost estimation is based on algorithmic models expressing relationship among different project parameters using mathematical expressions. Algorithmic models are parameter-based models and produce the best accuracy when these parameters are well defined and predictable. The fundamental factor governing project cost within algorithmic models is the software size, quantifiable either in lines of code or function points. Analogy based estimation and expert judgment-based estimation f
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Rakesh B S, Sujay K, and Anushree Raj. "SURVEY ON FACE DETECTION AND RECOGNITION ALGORITHMS USING DEEP LEARNING." In INFORMATION TECHNOLOGY & BIOINFORMATICS: INTERNATIONAL CONFERENCE ON ADVANCE IT, ENGINEERING AND MANAGEMENT - SACAIM-2022 (VOL 1). REDSHINE India, 2020. http://dx.doi.org/10.25215/8119070682.19.

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A facial recognition system uses a number of algorithms to recognize faces in digital photographs, identify people, and then confirm the authenticity of the acquired images by comparing them to facial images that have been saved in a database. Biometric technology is based on facial features of a person. Face detection and Recognition are major concerns in the area of biometric based systems and purposes. This process must ensure recognition accuracy and minimum processing time. Some cutting-edge techniques allow it to be retrieved more quickly in a single scan of the raw image and lie in a sm
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Singh, Baldev, and Surya Narayan Panda. "A Proactive Approach to Intrusion Detection in Cloud Software as a Service." In Achieving Enterprise Agility through Innovative Software Development. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8510-9.ch013.

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Cloud computing environment is very much malicious intrusion prone hence cloud security is very vital. Existing network security mechanisms face new challenges in the cloud such as DDOS attacks, virtual machine intrusion attacks and malicious user activities. This chapter includes brief introduction about cloud computing, concept of virtualization, cloud security, various DDOS attacks, tools to run these attacks & various techniques to detect these attacks, review of threshold methods used for detection of DDOS attacks & abnormal network behavior and proposed dynamic threshold based al
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Conference papers on the topic "Software based face antispoofing techniques"

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Kimbrough, Turhan, Pu Tian, Weixian Liao, and Wei Yu. "Performance of GAN-Based Denoising and Restoration Techniques for Adversarial Face Images." In 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA). IEEE, 2023. http://dx.doi.org/10.1109/sera57763.2023.10197680.

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Helfstein, Lucas, and Kelly Rosa Braghetto. "An Empirical Analysis of Data Drift Detection Techniques in Machine Learning Systems." In Simpósio Brasileiro de Banco de Dados. Sociedade Brasileira de Computação - SBC, 2024. http://dx.doi.org/10.5753/sbbd.2024.240606.

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Software systems with machine learning (ML) components are being used in a wide range of domains. Developers of such systems face challenges that are different from those of traditional systems because the performance of ML systems is directly linked to their input data. This work shows that ML systems can be improved over time by actively monitoring the data that passes through them and retraining their models in case of drift detection. To this end, we first assess some widely used statistical and distance-based methods for data drift detection, discussing their pros and cons. Then, we prese
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Fuentes, Arturo A., and Stephen Crown. "Enhancing the Teaching and Practice of Finite Element Analysis Using Asynchronous Computer-Based Instruction." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60423.

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Most engineering educators face complex, dynamic, pedagogical/cultural issues while teaching students. These issues include student motivation for the subject and self-direction, retention of information, integration of knowledge and adaptive expertise, and performance in projects and evaluations. They can be addressed by introducing modern learning strategies, expanding both the disciplinary breadth and the range of problems and problem-solving techniques to which engineering students are exposed, incorporating research experiences in the classroom, and effectively integrating the powerful so
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Wahba, Khaled, and Sherif Kamel. "A Virtual Research Model to Help Academics Face the Challenges of the 21st Century." In 2001 Informing Science Conference. Informing Science Institute, 2001. http://dx.doi.org/10.28945/2401.

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The academic career and the stages of promotion of teachers and field researchers at the Egyptian universities as well as at many research centers available in Egypt's 26 provinces is guided by a set of rules and regulations that mainly depend on the number of publications that the researcher is producing in a specific period of time. It is also important to note that such publications should be published in well-known and accredited journals, transactions, and conference proceedings amongst others. These publications could be produced jointly with other institutions both locally and internati
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Kalaitzi, Despoina, Evridiki Papachristou, and Spyridon Spiros Papadimitriou. "Architecture Techniques Merge with 3D Apparel Draping (to Create a Collection)." In 20th AUTEX World Textile Conference - Unfolding the future. Trans Tech Publications Ltd, 2022. http://dx.doi.org/10.4028/p-gm606z.

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The paper seeks to unfold the interrelationship and interaction between architecture and fashion disciplines. This research aims to explore ways of introducing architectural and computational tools into design processes of a fashion collection. In terms of methodology, the catalogue of the exhibition “RRRIPP!! Paper Fashion” which describes the history of paper garments was studied, in combination with an analysis of Iris Van Herpens’ parametric dresses via architectural diagrams. Different styles and the development of their patterns were also studied, overcoming the lack of pattern making an
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Wilson, Nathan M., Ana K. Ortiz, Allison B. Johnson, et al. "A Public Repository of Image-Based Computational Models for Patient-Specific Blood Flow Simulation." In ASME 2012 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/sbc2012-80916.

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Over the past two decades, significant progress has been made on increasing the realism and fidelity of image-based patient-specific blood flow simulation. A clear example of this progress is the first-of-a-kind multi-center clinical trial under way by Heartflow, Inc. (Redwood City, CA) attempting to utilize blood flow simulation in clinical decision making for coronary arterial disease. While recent applications of patient-specific blood flow simulation are impressive, numerous opportunities still exist for its application in advanced research in disease progression, design of better medical
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Su, Yi-Feng, Chih-Yuan Hsu, Yu-Chieh Wang, and Chung-Yu Yeh. "Image-Based Driver Status Monitoring System for Determining the Transfer of Dynamic Driving Tasks in Autonomous Vehicles." In WCX SAE World Congress Experience. SAE International, 2024. http://dx.doi.org/10.4271/2024-01-2397.

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<div class="section abstract"><div class="htmlview paragraph">Autonomous driving technology has advanced significantly in recent years, thanks to the innovations in vehicle design and artificial intelligence. This technology provides a more convenient and comfortable driving experience for both drivers and passengers. However, current autonomous driving systems still face some difficulties, such as the need for human intervention in critical situations. Switching control from the system to the driver without assessing their alertness or health status could pose a risk. Therefore, a
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Li, Hua, and Yiming Rong. "Unified Modeling Language and Object-Oriented Design Pattern Based Computer-Aided Welding Fixture Design System." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28294.

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Most of previous computer aided fixture design (CAFD) research has mainly concentrated on machining fixtures rather than welding fixtures, and how to face the challenges such as dynamic requirements, expansion, maintenance and management in the development of complicated computer aided welding fixture design (CAWFD) software system has received much less attention. Application of Unified Modeling Language (UML) and Object-oriented Design Pattern (OODP) for developing CAWFD software system has been discussed in this paper. CAWFD system functions like design phases, workflow and design subtasks
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Ahmed, Ali, Sadia Tasneem, and Ataur Rahman. "Challenges in application of statistical techniques in hydrology: A case study on regional flood modelling in southeast Australia." In International Conference on Advancements in Engineering Education. Science Technology and Management Crescent Australia, 2024. https://doi.org/10.71427/icaeed2025/35.

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Regional flood frequency analysis (RFFA) is the most widely used statistical technique to estimate design floods in an ungauged location using flood data recorded at nearby stream gauging stations. The application of statistical techniques in hydrology, particularly in RFFA modelling is challenging in Australia due to a higher degree of non-homogeneity. Statistical tools and techniques involve planning, designing, sampling, data collection, analysing (descriptive and inferential), interpretation, and reporting to conduct statistical hydrologic research. Besides these there are lots of statisti
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Dubovik, A. S., A. Y. Altynova, R. L. Khudorozhkov, A. A. Kozhevin, and D. V. Novikov. "Applied Generative AI and Deep Learning Techniques to Optimize and Automate Geophysical Workflows." In International Petroleum Technology Conference. IPTC, 2025. https://doi.org/10.2523/iptc-24677-ms.

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In the energy sector, traditional methods of subsurface data management and analysis face significant challenges that impact the efficiency and effectiveness of upstream oil and gas projects. Current approaches to seismic data processing and interpretation are often hindered by time-consuming manual processes, limited data accessibility, and fragmented workflows that struggle to integrate diverse data types. These limitations result in extended project timelines, increased operational costs, and potential oversights in critical geological interpretations, particularly when dealing with large-s
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Reports on the topic "Software based face antispoofing techniques"

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Heng, Kimkong. Cambodia’s Aspirations to Become a Knowledge-Based Society: Perspectives of Cambodian University Students. Cambodia Development Resource Institute, 2023. https://doi.org/10.64202/wp.138.202305.

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Background Cambodia envisages to become an upper-middle-income country by 2030 and a high-income country by 2050. The country also aspires to develop into a knowledge-based society (MoEYS 2014). To support these goals, it is crucial to consider the role of higher education institutions (HEIs), particularly universities, in training, research and service. However, research has shown that Cambodian higher education is faced with many challenges ranging from skills mismatches to fragmented governance to limited research capacity and stakeholder involvement (Heng and Sol 2022a; Kwok et al. 2010).
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Lunn, Pete, Marek Bohacek, Jason Somerville, Áine Ní Choisdealbha, and Féidhlim McGowan. PRICE Lab: An Investigation of Consumers’ Capabilities with Complex Products. ESRI, 2016. https://doi.org/10.26504/bkmnext306.

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Executive Summary This report describes a series of experiments carried out by PRICE Lab, a research programme at the Economic and Social Research Institute (ESRI) jointly funded by the Central Bank of Ireland, the Commission for Energy Regulation, the Competition and Consumer Protection Commission and the Commission for Communications Regulation. The experiments were conducted with samples of Irish consumers aged 18-70 years and were designed to answer the following general research question: At what point do products become too complex for consumers to choose accurately between the good ones
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