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70 articles for “robust face”
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Multi Face Detection and Gender Classification Based Attendance System
Abstract: Time management is critical in today's hectic classroom, and keeping track of attendance can take up valuable class time. Utilizing technologies like facial recognition and detection can greatly expedite this procedure. While face recognition algorithms compare the detected faces with known faces kept in a database, face detection algorithms can recognize human faces within a group photo or video stream. Without the need for human interaction, teachers can effectively record …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 1–7 Read article
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Review article on Quality Control in Clinical Trials
Abstract: Quality control (QC) is a critical component in the conduct of clinical trials, ensuring the accuracy, reliability, and credibility of data collected throughout the study. It encompasses a systematic set of procedures designed to monitor trial conduct and data integrity, thus safeguarding the rights, safety, and well-being of participants. This review explores the principles, implementation, and evolving practices of quality control in clinical trials, highlighting its importance across all phases …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article
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Challenges in Parallel Computing for Big Data Analytics
Abstract: The integration of parallel computing into the realm of big data analytics promises accelerated processing speeds and enhanced scalability, but it is not without its formidable challenges. This study explores the multifaceted hurdles faced in the pursuit of efficient parallel processing for large-scale data analytics. The intricate task of distributing and partitioning massive datasets across multiple processing units demands adept strategies to ensure equitable workloads. Load balancing emerges as a …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article
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CakeMeUp App: an E-commerce Solution for a Cake Shop
Abstract: This study introduces CakeMeUp, an innovative Flutter and Firebase-based e-commerce app for cake shop, offering sleek UI, real-time order tracking, secure payments, and cake customization. Integrating RazorPay and ikChatbot enhances functionality. It tackles e-commerce challenges, delivering a scalable platform for seamless online cake ordering. Implementation details, advantages, and key features are explored. CakeMeUp addresses common challenges faced in the e-commerce space by delivering a robust and scalable platform tailored for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 24–32 Read article
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Fingerprint and Face Recognition Based Attendance System for Exams
Abstract: In educational institutions, managing attendance efficiently and accurately is pivotal for ensuring academic integrity and administrative effectiveness. Traditional attendance tracking techniques, including human roll calls or barcode scanning, are laborious, error-prone, and vulnerable to fraud. Traditional methods of keeping track of attendance, including sign-in sheets and physical roll calls, are often time-consuming, prone to errors, and lack the security measures needed in many contemporary settings. Modern biometric technologies have made …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 3, 2024 · pp. 26–33 Read article
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Data Security in IoT
Abstract: Privacy and security are among the major Internet of Things (IoT) challenges. Improper device upgrades, lack of effective and robust security agreements, user ignorance, and popularity active device monitoring is among the challenges IoT faces. In this work, we explore the background of IoT applications and security measures, and identifying alternative security as well privacy issues, methods used to protect location components and IoT-based programs, existing security solutions, and the …
Published in Journal of Multimedia Technology & Recent Advancements Read article
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Zero Trust Implementation Challenges in Legacy and Wireless Network Systems
Abstract: This article titled "Zero Trust Implementation Challenges in Legacy Systems and Wireless Network Systems" delves into the evolving landscape of cybersecurity, emphasizing the inadequacy of traditional perimeter-based security models in the face of modern cyber threats. The Zero Trust Security framework is highlighted as an essential advancement in this scenario, emphasizing the core idea of "never trust, always verify." This paradigm shift underscores the importance of continuous verification, least privilege …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 39–50 Read article
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Real-time Operating Systems in the Era of IoT: Challenges and Solutions for Time-Critical Applications
Abstract: Real-time operating systems (RTOS) are essential in the Internet of Things (IoT), as they ensure timely responses to events, which is critical for the performance and reliability of connected devices. This paper delves into the unique challenges faced by RTOS in IoT environments, highlighting issues such as limited computational resources, strict latency requirements, and the increasing need for robust security mechanisms. The resource constraints inherent in many IoT devices, which …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 13–24 Read article
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Lyapunov-Stable Adaptive Fractional-Order Interval Type-2 Fuzzy Control for Robust Anti-Lock Braking Under Uncertain Road Adhesion Conditions
Abstract: This paper proposes a Lyapunov-stable Adaptive Fractional-Order Interval Type-2 Fuzzy Logic Controller (FO-IT2FLC) for robust anti-lock braking system (ABS) control under nonlinear vehicle dynamics and uncertain road adhesion conditions. The proposed framework integrates fractional-order error dynamics to capture memory-dependent tire–road interaction, interval Type-2 fuzzy inference to model uncertainty via footprint-of-uncertainty representation, and a Lyapunov-based adaptive learning mechanism for real-time parameter tuning. A rigorous stability proof guarantees boundedness of all closed-loop …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 Read article
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AI Enhanced E-Voting System Securing Elections with Face Recognition and OTP Authentication in India
Abstract: The E-Voting domain seeks to leverage technology to address these issues, enabling citizens to vote securely and conveniently while maintaining the transparency of the electoral process. Machine learning algorithms like Haar cascade and CNN will enhance the system's security, accuracy, and efficiency by leveraging data- driven approaches. Conventional voting techniques frequently encounter obstacles including identity theft, convoluted processes, and hold-ups in the processing of results. This article suggests a complex …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 21–30 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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Evaluation of Emergency Response Plans in Industrial Environments Using Simulation Techniques
Abstract: Industrial facilities, particularly those in the chemical, manufacturing, and energy sectors, face significant hazards due to their complex operations and the handling of hazardous materials. Ensuring the safety of workers and minimizing the impact of incidents require robust and effective emergency response plans (ERPs). Traditional evaluation methods, such as drills and tabletop exercises, often fall short in replicating the complexities of real-world emergencies. These methods may lack the realism needed …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 3, 2024 · pp. 6–10 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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OpenCV, AI, and Haar Cascade File: A Review
Abstract: Real-time image processing applications using OpenCV encompass a diverse and crucial array of tasks in modern technology. OpenCV's robust capabilities enable the implementation of object detection and tracking, which are vital for surveillance systems to monitor and analyze activities in real time. In the realm of security, face recognition technology, powered by OpenCV, provides accurate and efficient identification and authentication, enhancing safety measures. Gesture recognition, another significant application, facilitates intuitive …
Published in Journal of Open Source Developments · Vol. 11, Issue 2, 2024 · pp. 39–46 Read article
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Live Integrated Facial Observation (L.I.F.O.)
Abstract: A human face is the most influential part of humans that can uniquely identify a person. Using all the facial characteristics as biometric, the LIFO system can be applicable in many different ways. Like in everyday life, the most mandatory task in any organization is attendance marking. Earlier, people used to mark their presence using paperwork but now along with the advancement of technology, this system has also changed and …
Published in Journal of Advancements in Robotics Read article
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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A Survey on Cognitive Radio Ad Hoc Network Architecture
Abstract: Cognitive radio ad hoc networks (CRAHNs) represent an innovative paradigm in wireless communication, leveraging the dynamic spectrum access capabilities of cognitive radios (CRs) to enhance network performance and spectrum efficiency. The architecture of CRAHNs integrates cognitive radio capabilities with ad hoc networking principles, enabling devices to manage spectrum resources autonomously and intelligently in a decentralized manner. This abstract outlines the key components and functionalities of CRAHN architecture, highlighting its potential …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 1–7 Read article
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Securing AI: A Survey Addressing Cyber Threats Arising in Cyber Security Due to Artificial Intelligence
Abstract: In today’s ever-evolving technological landscape, the integration of Artificial Intelligence (AI) across various industries underscores the critical need for a robust cybersecurity framework. This comprehensive survey delves into the pressing necessity of safeguarding AI systems against cyber threats. Recent incidents have highlighted the alarming susceptibility of AI to malicious attacks, showcasing the potential repercussions of compromised systems. These attacks range from data manipulation to privacy infringements, posing significant risks to …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 41–49 Read article