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344 articles for “Feature Detection”
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RFID Based Smart Trolley Billing System Using IoT
Abstract: Customers experience better retail interactions while operations become more efficient in the modernizing retail industry. Shopping through traditional methods requires lengthy manual scanning for products and billing operations leading retailers to require automation solutions for streamlining these processes. This system consists of RFID detection alongside 8051 microcontroller processing and load cells monitoring and uses IoT communications and relay controls to power an intelligent automated shopping cart. Real-time data tracking functions …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Study on Brain Tumor Detection Using Morphological Operations in MATLAB with Graphical User Interface (GUI)
Abstract: Brain tumor detection plays a crucial role in early diagnosis and effective treatment planning. This research presents a MATLAB-based Graphical User Interface (GUI) for Brain Tumor Detection, incorporating a comprehensive pipeline of image processing techniques. The GUI provides a user-friendly platform, empowering medical professionals to accurately and efficiently analyze MRI brain scans. The GUI begins with text removal to eliminate any textual artifacts that may be present in the MRI …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 24–31 Read article
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Machine Learning Techniques for Early Detection of Heart Disease
Abstract: Cases of heart disease are increasing rapidly, thus it's important and concerning to be aware of any potential ailment beforehand. This diagnosis is a difficult task that must be completed fast and precisely. The primary goal of this study is to determine which patient, based on different medical features, has a higher chance of having heart disease. We created a heart disease prediction algorithm based on the patient's medical history …
Published in Journal of Microelectronics and Solid State Devices · Vol. 10, Issue 3, 2023 · pp. 16–21 Read article
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AI based Assistive glasses for visually impaired persons
Abstract: There been a lot of change in tools for assisting visually impaired persons from simple analog tools to digital sensor-based devices. In this paper we have designed an AI- based smart assistive glass which can detect objects, read text their nature, distance and give feedback through audio output in real time. This system stores visual data and with use of object recognition it analyzes surroundings.Besides,VL53L0X TOF mea- sures accurate distance …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 22–29 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Inspection of Objects using Computer Vision
Abstract: This study is motivated mainly by the need for more efficient and advanced techniques in an inspection of an object because accurate and timely information is needed for any industry to improve their quality and increase the production of goods. The objective of this study is to provide an inexpensive and comprehensive review of defect inspection techniques. Nowadays, new computer vision technologies and image processing technologies have been very important …
Published in Journal of Electronic Design Technology · Vol. 11, Issue 3, 2020 · pp. 6–16 Read article
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Comparative Analysis of a Lie Detector using Support Vector Machine, Naive Bayes, and Random Forest Algorithm with Speech to Text Conversion
Abstract: Lie detection, additionally known as deception detection, uses questioning techniques to determine truth and falsehood in response. Physiological responses like vital sign, blood pressure, heartbeat, and respiratory rate are used to discriminate between truth and lie. Once we lie, our blood pressure goes up, our heart beats quicker, we have a tendency to breathe faster (and our breathing slows once the lie has been told), and changes occur in our …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 1, 2021 · pp. 13–18 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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Voice Controlled Wheelchair Along with Health Monitoring
Abstract: In recent years, mobility aids like wheelchairs have been essential for enhancing the independence of individuals with physical disabilities. However, traditional wheelchairs, often controlled manually or via joysticks, pose challenges for those with severe impairments. This project introduces a voice-controlled wheelchair integrated with health monitoring capabilities, addressing these limitations. The system features an ESP32 microcontroller that processes voice commands, such as "move forward" or "stop," captured by a microphone and …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
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Power Quality Monitoring in Wind Solar Hybrid System
Abstract: With the development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 1, 2018 · pp. 16–23 Read article
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Optical Image Sensing and Analysis of Iron Ore Pellets: A Machine Learning Approach
Abstract: The present work is aimed to improve quality control in steel production using SEM imaging and machine learning. High-resolution SEM images of iron ore pellets, primarily composed of hematite and magnetite, are analyzed to understand their microstructural features, which significantly impact pellet performance during reduction processes. Traditional microstructure analysis is manual, time- consuming, and prone to inconsistencies. This study proposes an automated approach using K-Means Clustering, Canny Edge Detection, DBSCAN, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 7–18 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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Plc Hmi base testing machine data loger with usb excel data export
Abstract: The PLC-HMI-based testing machine data logger is designed to acquire, process, and log real-time sensor data using a PLC analog input card. This system is developed for industrial applications requiring accurate measurement, monitoring, and data storage. The setup integrates an HMI (Human-Machine Interface) for visualization and control, while a USB-based Excel data export feature ensures efficient data management. The system incorporates four key transducers: 1. Water Flow Sensor – Measures …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 47–54 Read article
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Classifying Abnormalities in Heartbeat Sound
Abstract: Heartbeat sounds play a major role in the detection of various diseases such as heart disease, hyperthyroidism, and high blood pressure in their early stages. In the proposed method, various abnormal and healthy heartbeat audio signals are given as input and the features are extracted using MFCC (mel-frequency cepstral coefficients). Then, a deep learning approach is applied in which the MFCC audio signals are sent to the CNN (convolutional neural …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 24–31 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Monitoring of Unauthorized Identity and Access Behaviour for Outsourced Data in Cloud Environment
Abstract: The outsourcing of data is a significant challenge in the modern cloud computing ecosystem when it comes to tracking unauthorized identification and access behaviour. In order to overcome this issue, this research suggests a thorough method for reliable anomaly detection in cloud systems. Improving data security and offering a trustworthy monitoring system are the two main goals. The suggested approach proceeds methodically, gathering information from several sources such as user …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 9–19 Read article
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Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article