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438 articles for “Detection Techniques”
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AI-Powered License Plate Recognition
Abstract: With the number of cars multiplying daily, safety precautions are judged required. Automatic number plate recognition uses image processing and machine learning techniques to recognize vehicle numbers. By utilizing the vehicle number plate, the approach recommended seeks to establish a capable automated approved auto identification system. We describe an automated vehicle number detection system based on image processing and Raspberry Pi that reads license plates. In this setting, a Raspberry …
Published in Trends in Machine design · Vol. 11, Issue 1, 2024 · pp. 20–29 Read article
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Understanding Food Spoilage: Mechanisms, Shelf-Life Determination, and Safety Standards
Abstract: Food spoilage poses significant challenges to the global food industry, impacting both food safety and economic sustainability. The main causes of food quality deterioration are microbial and non-microbial spoiling. Microbial spoilage primarily results from the activity of bacteria, yeasts, and molds, which thrive under favorable environmental conditions. These microorganisms can lead to food poisoning and spoilage through the production of off-flavors, discoloration, slime formation, and the accumulation of harmful toxins. …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 14, Issue 1, 2025 · pp. 6–9 Read article
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Toxicology-Focused Development and Validation of an RP-HPLC Technique for Quantifying Bempefoic Acid and Rosuvastatin in a Fixed-Dose Combination
Abstract: A straightforward, precise method was developed to simultaneously assess Bempedoic acid and Rosuvastatin in both bulk and tablet forms. Utilizing a DIKMA Spursil C18 column (4.6 mm x 250 mm, 3.0 μm), chromatography was conducted with a mobile phase comprising 30% phosphate buffer and 70% acetonitrile, flowing at 1 ml/min. Operating at ambient temperature, the optimized wavelength for detection was set at 240 nm, revealing retention times of 4.418 min …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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Real Time Automobile - Caused Air Pollution Monitoring System
Abstract: The system proposed in this paper aims to be a novel approach for real-time detection and quantification of vehicular emissions, integrated into smart city infrastructures. The structured workflow enhances accuracy and efficiency. The license plate is captured by OCR, while the ground clearance is simultaneously measured, allowing the thermal camera to dynamically adjust its position to align with the tailpipe level. The emission data is collected and transmitted to a …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 49–55 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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Image Preprocessing and Analysis on Eye Fundus Images Segmentation by Using Density Clustering Methods
Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, so …
Published in Recent Trends in Sensor Research & Technology 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 Comparative Study Between GSM and CNN to Develop Gesture Detection Based Alert System for Women Safety
Abstract: Women’s safety is a pressing issue in today’s world, and technology can play a crucial role in addressing it. This project introduces a facial expression recognition device that uses Convolution Neural Network (CNN) technology and develop it’s comparison with an expression system with use of GSM is done. Unlike traditional methods relying on manual activation or dedicated devices, this system reacts instantly to threatening situations by recognizing predefined gestures, ensuring …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 1, 2024 · pp. 24–30 Read article
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Cybersecurity in a Digital World: Risks and Future Perspectives
Abstract: The field of information security offers a wide range of guidance in academic and practitioner literature. While various strategies such as deterrence, deception, detection, and reaction are explored, most research focuses on technological countermeasures to prevent security threats. This study presents the findings of a qualitative study conducted in Korea, examining how businesses utilize security techniques to safeguard their information systems. The results highlight a strong emphasis on preventive measures, …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 44–49 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Extraction and Compound Analysis of Bauhinia acuminata: Soxhlet Method and Identification
Abstract: In the present study, the extraction and compound analysis of Bauhinia acuminata using the Soxhlet method, coupled with identification techniques, were conducted. Bauhinia acuminata L., a member of the Leguminosae (Fabaceae) family in the Caesalpinioideae subfamily, is a shrub usually reaching a height of around 3 m. It is native to tropical Southeast Asia and commonly found in the tropical regions of India and China. Primarily grown for ornamental purposes, …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 2, 2024 · pp. 18–23 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 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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Optimizing Image Processing with Verilog on FPGA: Techniques and Performance Enhancements
Abstract: The integration of image processing algorithms into hardware platforms, particularly FPGAs, presents a compelling opportunity for achieving high performance, low latency, and power efficiency in real-time applications. This study focuses on designing and implementing Verilog HDL-based optimal image processing methods for FPGA-based systems. The study explores the development of core algorithms, including edge detection, image enhancement, and adaptive filtering, to maximize resource utilization and processing speed on hardware platforms. Key …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 3, 2024 · pp. 46–53 Read article
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Unraveling Metagenomics: A Comprehensive Diagnostic Approach for COVID-19
Abstract: The COVID-19 pandemic has brought attention to the need for rapid, accurate, and scalable diagnostic techniques. Metagenomics, a powerful technique that enables the comprehensive analysis of genetic material from complex microbial communities, has emerged as a promising diagnostic approach for COVID-19. This article elucidates the principles of metagenomic sequencing, highlighting its ability to detect viral RNA directly from clinical samples without prior knowledge of the pathogen. Furthermore, we discuss the …
Published in International Journal of Tropical Medicines · Vol. 1, Issue 2, 2024 · pp. 19–28 Read article
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Efficient Cell Balancing and Protection Schemes for Electric Vehicles
Abstract: Efficient cell balancing and protection are critical aspects of electric vehicle (EV) battery management systems, ensuring optimal performance, longevity, and safety. Cell balancing refers to the process of equalizing the charge levels of individual cells within a battery pack to maximize energy utilization and prevent overcharging or undercharging of any cell. This promotes uniform wear and extends the overall lifespan of the battery pack. In the context of EVs, where …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 9–21 Read article
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Advancing EEG Technology for Affordable and Effective Epilepsy Detection
Abstract: For a proper diagnosis and prompt treatment, epilepsy, a neurological condition marked by recurring seizures, needs to be continuously monitored. Manual interpretation is frequently used in traditional approaches for identifying epileptic seizures from electroencephalogram (EEG) signals, which can be laborious and error-prone. In this research, a novel method for automatically detecting epilepsy from EEG data using deep learning algorithms is presented. According to centers for disease control and prevention (CDC) …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 11–18 Read article
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Optimizing Chromatographic Techniques for Comprehensive Paraben Analysis to Enhance Safety in Consumer Products
Abstract: Parabens (PBs), such as methylparaben (MePB), ethylparaben (EtPB), propylparaben (PrPB), and butylparaben (BuPB), are widely used as preservatives in pharmaceuticals, food, and personal care products due to their antibacterial properties. However, there are growing worries about their potential to disrupt hormonal functions, which has led to stricter regulations. This study focuses on creating a robust high-performance liquid chromatography (HPLC) method for quickly measuring all four parabens in consumer goods. We …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 228–243 Read article
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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article