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1245 articles for “Detection”
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IoT Innovations in Power System Monitoring: Reviewing Transmission Line Multiple Fault Detection Systems
Abstract: In this review, it is possible to highlight a new project idea called Transmission Line Multiple Fault Detection System with Internet of Things (IoT). It is a IoT based research that helps in identifying multiple failures on transmission lines leading to fast and correct response. It consist of installing many senors of different types like temperature sensors, current sensors, and vibration sensors on the lines in order to carry out …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 1, 2024 · pp. 20–28 Read article
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Smart Home Safety Using Fire and Gas Detection System
Abstract: In a world where technology is advancing at a rapid pace, one goal of smart homes is to protect the safety of the house and, most importantly, the people who live there. An essential part of our suggested systems' functionality is the inclusion of fire and gas detection sensors. The increasing use of smart homes has shown new ways of increasing security and safety through including intelligent techniques in proper …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 35–43 Read article
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Design and Implementation of an IoT-Based Power Theft Detection System Using Sensor Networks
Abstract: With the increasing demand for efficient energy distribution and consumption monitoring in smart grid systems, the need for robust power theft detection mechanisms becomes paramount. This project proposes an IoT-based solution utilizing energy metering to detect instances of power theft within different segments of the distribution network. The system employs three types of energy meters: Distribution Point (DP), Pole, and Domestic meters. Every meter is positioned thoughtfully to track the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 2, 2024 Read article
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Comparative Study of Change Detection Methods in High Resolution Images
Abstract: Natural phenomena including weathering, erosion, volcanic eruptions, and plate tectonics, as well as human activities like agriculture, deforestation, and urbanization, cause the Earth's surface to change continuously. In many different applications, such as environmental monitoring, disaster management, urban planning, agriculture and forestry, climate change studies, resource management, and infrastructure monitoring, it may be extremely beneficial to detect and track these changes. There are various algorithms and methods proposed by many …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 1–5 Read article
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Comparative Study of Facial Spoofing Detection using CNN Architecture
Abstract: Facial recognition systems face a high risk of security breach due to various facial spoofing attacks. This challenge was addressed by the study of several deep learning models. This study proposes an idea to detect facial spoofing using deep learning architecture to differentiate live faces form various types of spoofed images/videos using different CNN models. In addition, the study seeks to strengthen security measured in facial recognition system demonstrating that …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 9–17 Read article
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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An Evaluative Comparison of CD123 and CD66c as Biomarkers to Detect Minimal Residual Disease in B-Cell Acute Lymphoblastic Leukemia
Abstract: Background: B-cell Acute Lymphoblastic Leukemia (B-ALL) often shows lineage heterogeneity with lymphoid cells expressing myeloid markers. Minimal Residual Disease (MRD) refers to the small number of cancer cells that may remain in a patient's body after treatment and that are undetectable by standard diagnostic methods. In diseases like B-cell Acute Lymphoblastic Leukemia (B-ALL), MRD is a critical prognostic indicator, as its presence can signal a higher risk of relapse. In …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 7–12 Read article
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Advancements in Nanotechnology and Biosensor Integration for Detection and Treatment of Alice in Wonderland Syndrome
Abstract: Alice in Wonderland Syndrome (AIWS) is an uncommon neurological condition characterized by profound distortions in perception. Individuals with AIWS experience altered body image and spatial awareness, often perceiving objects, surroundings, or even their own body as being unusually large, small, or distorted. The condition presents a unique challenge for both diagnosis and management due to its elusive and varied symptoms. This paper explores how advancements in nanotechnology and biosensor integration …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 3, 2024 · pp. 1–12 Read article
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Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Deep Learning Meets IoT: Hybrid Approaches for Botnet Detection
Abstract: Rapid advancement in the Internet of Things (IoT) changed everything, making it possible for seamless interconnectivity of devices and altering data-driven decision processes. This study delves into the intersection of IoT with deep learning approaches and hybrid approaches for managing botnet in IoT systems, especially security, efficiency, and performance optimization. Leveraging deep learning models, for example, CNNs and RNNs, will help the network achieve more intrusion detection and data analysis. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 18–27 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 Read article
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Sensor Guard: Thermal Sensor System for Lion Detection and Collision Prevention
Abstract: This paper presents a novel system that utilizes thermal imaging and CCTV cameras integrated with sensors to detect heat sources, specifically focusing on the detection of lions near railway tracks to prevent collisions. The system employs infrared thermal imaging to identify heat signatures of animals, particularly lions, that may create risk to his/her life. By combining thermal sensors and machine learning algorithms, the system is capable of accurately the heat …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 21–28 Read article
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Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Abstract: It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. Most people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 15–20 Read article
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Face Detection and Classification for Attendance Systems on Android
Abstract: This work offers a facial recognition-based attendance system with the goal of addressing the drawbacks of traditional manual attendance. The manual attendance procedure can be made more efficient by using facial recognition technologies and mobile platforms. This design is divided into three function modules: attendance sign-in, attendance record, and face recognition system of check on work attendance information input. It also introduces a face detection and classification principle, analyses the …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 15–22 Read article
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Integrating Internet of Things and Global Navigation Satellite System for Advanced Accident Detection and Road Safety Enhancement
Abstract: The purpose behind this project is to improve road safety through the development of an innovative internet of things (IoT)-based accident detection and reporting system. This research paper proposes the integration of GSM (Global System for Mobile Communications) and LoRa (long-range communications) technologies, utilizing the A9G module, Arduino Nano, and LoRa module RA02, to achieve real-time accident detection and efficient reporting. By leveraging accelerometer data analysis, the system promptly identifies …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 1, 2025 · pp. 29–35 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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A Comprehensive Survey on Detection of Video Transitions
Abstract: Video shot boundary detection (SBD) is a fundamental task in the field of video processing and analysis. It plays a critical role in various video applications such as content-based video retrieval, video indexing, editing, summarization, and browsing. Identifying shot boundaries helps segment a continuous video stream into distinct shots, each representing a meaningful visual unit. This segmentation is essential for organizing and interpreting video data efficiently. This study provides an …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 17–26 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article