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1245 articles for “Detection”
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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Genetic Detection of Hepatitis C -Virus and Occult Hepatitis B in Patients from Al-Najaf Al-Ashraf Governorate, Iraq.
Abstract: Recently, a noticeable increase in the prevalence of occult Hepatitis B virus (HBV) and Hepatitis C virus (HCV) infections has been observed among clinical cases such as patients undergoing hemodialysis, blood transfusion, liver diseases, and thalassemia worldwide. To limit and control this spread, the present study was conducted to investigate and detect the molecular presence of HCV and occult HBV using the Nested PCR technique, as well as to observe …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 1, 2026 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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Intelligent Polymer-Integrated Wearable Platforms for Sustainable IoT and Predictive Health Monitoring for Migraine Detection
Abstract: Migraine is a neurological disorder, and its effect on the global workforce is resultantly significant. However, the fact of the matter is the absence of notable technological breakthroughs and the fact that the technology presently available is reactive, meaning it tackles the symptoms of the attack after the attack has occurred. The requirement for this paper is, therefore, the provision of an innovative approach, and this paper will describe the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 946–960 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Detection of Stator and Rotor Winding Faults in Induction Motor using Park’s Vector Approach
Abstract: The Induction Motors in every rotating machine’s heart and it’s a very important component in a much. Almost 90 percent of the Induction Motor use in industry as a prime mover. So Induction Motor is necessary to Condition Monitoring for Economic Running Cost. Condition Based Monitoring of Induction Motor has become an important and difficult task for Engineers and Researchers mainly in Industrial applications. Several Condition Monitoring Methods (Technique) including …
Published in Journal of Control & Instrumentation Read article
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Hawk Eye Detection System (Using Python)
Abstract: Tennis and cricket are gaining popularity. Hawk eye is a modern tool that can be applied to any sport. Now a days there is lots of advancement in the sports technology. Hawk Eye first gained notoriety in television broadcasts of cricket. Broadcasters used Hawk-Cricket Eye's System at the 2006 ICC Champions Trophy in India, the World Cup, and important Test and ODI series all over the world since 2001. A …
Published in Journal of Multimedia Technology & Recent Advancements Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Detection of Driver Emotion Using Deep Learning
Abstract: High level Driver-Help Frameworks (ADASs) are utilized for expanding security in the auto space, yet momentum ADASs quite work without considering drivers' states, e.g., whether she/he is genuinely able to drive. Feelings are a significant way of behaving of people and may emerge in driving circumstances. Uncontrolled feelings can prompt unsafe impacts. To control and decrease the adverse consequence of conduct. In this paper we will distinguish the driver’s conduct. …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 01–06 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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Development of Hybrid Detection and Alert mechanism for Women Safety using AI
Abstract: The integration of AI-based smart surveillance systems in enhancing women's safety and security has been a focal point of research and development. This literature study explores the impact of information technology advancements, particularly in the realm of mobile applications, GPS tracking, and social media platforms, on improving women's safety. Noteworthy contributions include the development of apps such as Circle of 6 and Be Safe, which offer women immediate access to …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 1, 2024 · pp. 36–46 Read article
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Ransomware Detection and Prevention Using Honeypot
Abstract: The significance of network security and explores the details of ransomware attacks, highlighting the crucial parameters essential to fortifying defences against this pernicious cyber threat. Network security involves safeguarding computer networks against unauthorized access, data breaches, and cyberattacks. Ransomware attack, a specific type of cyberattack, entail malicious software encrypting a computer system, making them unavailable to use in return attacker asks for ransom in form of cryptocurrency like Bitcoin or …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 8–13 Read article
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: vcmn
Published in Current Trends in Signal Processing · Vol. 1, Issue 2, 2025 Read article
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Smart Vehicle Security System Using Fingerprint Authentication with Alcohol Detection
Abstract: An electronic device is installed in a car or fleet of vehicles as part of a vehicle tracking system, which allows the owner or a third party to follow the whereabouts of the vehicle while also gathering data. The technology known as a modern vehicle tracking system (VTS) uses a variety of techniques, including GPS and GSM modules as well as other radio navigation systems that employ satellites and ground-based …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 1, 2024 Read article
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Smart Train Station System: An IoT- Powered Platform with Arrival Detection
Abstract: The primary objective of this paper is to provide platform users with timely arrival status information and automate pedestrian crossing of the railroad tracks without the need for a staircase. This approach aims to mitigate potential accidents, particularly significant in regions like India where train accidents are more prevalent. Using IR transceivers, it determines each tsrain's state and notifies the micro controller about it. By using this research to prevent …
Published in Journal of Microelectronics and Solid State Devices · Vol. 11, Issue 1, 2024 · pp. 32–38 Read article
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Developing a Comprehensive Framework for User and Entity Behavior Analytics (UEBA): Integrating Advanced Machine Learning and Contextual Insights
Abstract: User and Entity Behavior Analytics (UEBA) has emerged as a crucial approach in modern cybersecurity for detecting and mitigating insider threats, compromised accounts, and other malicious activities within organizational networks. However, existing UEBA frameworks often face challenges in scalability, detection accuracy, and response effectiveness. This research work proposes a novel framework for UEBA that aims to address these limitations and enhance threat detection and response capabilities. The framework integrates advanced …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 20–32 Read article
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A review of the employing of Wavelet transforms and Classifier Artificial intelligence (AI) methods for detecting power transmission difficulties
Abstract: Power systems use large interconnections to transmit and distribute electric power. For power transmission, the same voltage levels are used for minimum transmission losses. During power transmission faults may occur due to natural events such as lightning, strong wind, fire etc. Faults may occur between phase conductors to ground or between the phase conductors. Transmission line protection has been performed using the comparison of voltages and currents and activates the …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 2, 2024 · pp. 36–41 Read article
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Yoga Posture Detection and Correction
Abstract: Our project introduces a pioneering method for enhancing yoga practice through real-time pose correction, utilizing cutting-edge computer vision technology. Originating in India 5000 years ago, yoga offers profound benefits for both body and mind, yet with the modern lifestyle's increasing stress levels, its popularity has surged globally. While various avenues exist for learning yoga, including classes at yoga centers and self-learning through books and videos, many individuals struggle to identify …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Avian Echoes: Convolutional Neural Network for Bird Vocalization Detection
Abstract: Bird species identification is a complex task within ornithology that demands advanced technological solutions. This research presents an approach leveraging Convolutional Neural Networks (CNNs) for bird species recognition based on identification of bird sound, each employing unique datasets and methodologies. The objective involves a two-stage identification process, beginning with the construction of an ideal dataset. The crucial step involves converting 1D audio waveforms to 2D spectrograms, enhancing CNNs' ability to …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 26–37 Read article