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1987 articles for “Lap Splice Detection” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Fingerprint Liveliness Detection in Biometric Authentication: A Survey
Abstract: In the world of cyberspace, presentation attacks (PA) on biometric systems have grown to be a major worry. The review of the literature suggests that these systems are more susceptible to spoofing or presentation attacks (PAs), which frequently cause the authentication or identification system to completely fail. To combat against presentation attacks (PAs), the presentation attack detection (PAD) or antispoofing methods have been developed to validate the liveness of the …
Published in Journal Of Network security · Vol. 10, Issue 2, 2022 · pp. 9–13 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Cell Phone Detector
Abstract: This project presents a Solar-Powered Cell Phone Detector—an innovative and eco-friendly system designed to detect active mobile phones using renewable energy. The primary goal is to offer a sustainable, off-grid solution for environments where mobile phone usage must be restricted, such as examination halls, confidential meeting rooms, and high-security zones. Traditional detectors typically rely on conventional power sources, making them less practical during outages or in remote areas. This system …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 3, 2025 · pp. 7–13 Read article
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Implementation of Kalman Filter Using TDC and PLL for Object Detection and Tracking in Signal Processing
Abstract: The measurement uncertainty of GPS receivers is dependent on a wide range of external factors, including receiver clock precision, thermal noise, atmospheric influences, and minute variations in satellite positions. Estimating hidden states precisely and accurately in the face of uncertainty is one of the main problems facing tracking and control systems. Among the most significant and widely used estimate methods is the Kalman Filter. It uses imprecise and erratic measurements …
Published in Current Trends in Signal Processing · Vol. 13, Issue 2, 2023 · pp. 38–47 Read article
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Object Detection Using Deep Learning Algorithm
Abstract: Object detection is a computer technology related to computer vision and image processing that deals with detecting images of semantic objects of a certain class (for example cars, buildings, etc.) in digital images and videos. To detect objects, there are many algorithms available, in this paper YOLO algorithm is explored for detection of objects on real-time data. You Only Look Once (YOLO) is a state-of-the-art real time object detection system …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 1–13 Read article
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Traffic Congestion Detection among Manual and Autonomous Vehicles using AHP Algorithm
Abstract: Autonomous vehicles (AVs) are the newest intelligent transportation system (ITS) solutions that can move without human intervention. These goodscontinue their trajectory with a variety of sensors comprising various components. Utilizing these technologies effectively within the logistics businessmight generate a competitive advantage. There are numerous AVs on the market today, with some being superior to others in terms of build quality, range of functions, and design. Choosing an efficient, optimal, and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 3, 2022 · pp. 8–15 Read article
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Age, Gender And Emotion Detection
Abstract: The main reason is the development of a method to automatically estimate the age and gender of the human face. It continues to play an important role in computer vision and pattern recognition. In addition to age determination, facial emotion recognition also plays an important role in computer vision. Nonverbal communication methods such as facial expressions, eye movements, and gestures are used in many human-computer interaction applications. Much research has …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 1–6 Read article
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An Exploration on Data Mining for Face Detection based on Real time Face Tracking
Abstract: AbstractData mining has been extensively used to gather meaningful information and to improve the significant relationship for the variables warehoused in large data stores. Machine learning provides the technical basis of data mining. Automatic face recognition research which try to give the computer ability to recognize face to distinguish characters. As a key technology of biometrics face recognition technologies, in public security, information security, financial, and other fields has potential …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 3, 2014 · pp. 46–51 Read article
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An Abnormal Expression Detection System (AEDS) Using Deep Learning Algorithms
Abstract: In the last decade, many deep learning algorithms have achieved remarkable success and gained popularity in various computer vision tasks, including object detection, image recognition, and segmentation. This AEDS (Abnormal Expression Detection System)leverages the power of deep learning algorithms to detect abnormal facial expressions in real-time automatically. AEDS proposed two important models; those are Deep CNN and RNN. CNN is responsible for learning discriminative features from facial images and capturing …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 72–79 Read article
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Real-world Pothole Detection Using Image Processing and Deep Learning Convolutional Neural Network Model
Abstract: Potholes are a major problem of concern in many parts of the cities across the country. Road accidents are one of the causes that significantly affect humanity and result in damage to vehicles and road surface. Potholes are dangerous for pedestrians who walk along the road and vehicular traffic on busy roads. Road accidents are caused due to improper maintenance of roads, and it is imperative to attend to such …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 95–103 Read article
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A Review on Segmentation Approaches for Brain Tumor Detection
Abstract: It is commonly said statement ‘the health is wealth’, so if you are healthy then everything is with you. Although everyone takes care of their health in their own ways but some diseases are not under the control of the human being.The “tumor” is one of the crucial diseases which is till now, out of control, in which brain tumor is again a serious issue. The most crucial job which …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 1, 2021 · pp. 6–12 Read article
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Intrusion Detection Using ANN Machine Learning for MIM, DOS, BO
Abstract: Intrusion detection system is a software program developed to use on computer systems so that it can identify intrusion attack with help of different techniques like the machine learning algorithms. The variety of assaults over the internet has multiplied through the years because of the development and smooth availability of computing technologies. Attackers develop new attack types, so in order to save you from those assaults, intrusion detection systems must …
Published in Journal Of Network security Read article
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Guardian of the Sky: Drone Detection and Jamming Technology
Abstract: India has reported remarkable growth in drones in the past ten years for both commercial and defense uses that led to extremely intricate problems. Systems operate as the major onset of the risks involved that might be associated with drone operations. This article provides a comprehensive evaluation of counter-drone systems, with a particular focus on two fundamental aspects: radar targeting, tracking, and other technologies. The main objective of the study …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 2, 2024 · pp. 19–25 Read article
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Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning
Abstract: This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 9–18 Read article
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Comparative Efficacy of Hybrid Capture 2 and Real-Time PCR in Detecting High-Risk HPV Genotypes for Cervical Cancer Screening
Abstract: Human papillomavirus (HPV) infection is a leading cause of cervical cancer, making early detection critical for effective prevention and treatment. Among the diagnostic methods available, Hybrid Capture 2 (HC2) and Real-Time Polymerase Chain Reaction (PCR) are widely used for detecting high-risk HPV genotypes, particularly HPV 16 and 18, which account for the majority of cervical cancer cases. This review aims to compare the efficacy of HC2 and Real-Time PCR in …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 2, 2024 · pp. 13–17 Read article
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Intrusion Eye Detector
Abstract: Uncertainty about security risks and illegal access are becoming more prevalent in a variety of settings, such as private homes, business buildings, and critical government buildings. Conventional security systems, which may not offer real-time warnings or prompt reactions, frequently rely on passive monitoring, including CCTV cameras and motion sensors. Artificial intelligence (AI) and computer vision-based intelligent systems are becoming more and more popular as a means of improving security and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 28–32 Read article
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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A Study on Recent Trends in Chemical Sensors for Detecting Toxic Materials
Abstract: Poisonous materials, such as mutagenic, carcinogenic, and poisonous compounds, are widely produced as a result of industrial development. Such materials continue to be hazardous to human health despite stringent management and control procedures. As a result, practical chemical sensors—such as optical, electrochemical, nanomaterial-based, and biological system-based sensors—are needed for the monitoring of dangerous chemicals. For the detection of harmful compounds, numerous new and existing chemical sensors are being created, along …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 3, 2025 · pp. 26–35 Read article