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532 articles for “detection methods”
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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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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IoT-Based Structural Health Monitoring and Damage Detection in Fiber Reinforced Polymer Composite Structures
Abstract: Applications of fiber-reinforced polymer (FRP) composite in the aerospace, civil infrastructure and renewable energy systems are increasing due to the fact that the composite possesses high ratio of strength to weight and can resist corrosion. However, processes of internal damages such as the cracking of the matrix, delamination and fiber fracture, are likely to take place without being visible on the surface and therefore a periodic check of the structure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1076–1100 Read article
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Association of Vitamin D Binding Protein BP rs2282679 Gene Polymorphism and Serum Levels of Vitamin D in Patients with Vitiligo
Abstract: For vitamin D to have an impact, the vitamin D receptor (VDR) must be expressed and activated in the nucleus. The VDR has several known genetic variants. Biological impacts can be caused by changes in DNA sequences known as "polymorphisms" that are common in the population. Vitiligo is a disease that causes loss of skin color in patches, and it is a chronic (long-lasting) autoimmune disorder loss of color. The …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 2, 2024 · pp. 45–52 Read article
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Gas Sensors Fabricated using Carbon Powder Derived from Dried Banana Peels Waste to detect Methanol, Ethanol, Acetone Vapors and Carbon Dioxide Gas
Abstract: Low cost and environmentally friendly activated carbon powder was synthesized using waste banana peels. Phosphoric acid was utilized as activation agent. Doctor blade method was employed to fabricate films of activated carbon on conductive or nonconductive glass substrates. Films were subsequently annealed at 70 0C for 30 minutes in air. According to XRD patterns, single phase of activated carbon was crystallized in thin film form. Carbon prepared from banana peels …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 14–25 Read article
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Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
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Detectiverse: Advancing Supply Chain Efficiency with AI-Enhanced Screw Counting
Abstract: Accurate screw counting is essential in the manufacturing sector to ensure efficient inventory management and maintain quality control standards. The current manual counting method is prone to errors and lacks the ability to identify the source of missing screws. To address this challenge, we propose implementing an automated screw counting system at Indo Metal Tech in Ambattur, Chennai. This system would utilize advanced image processing and machine learning algorithms to …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 21–26 Read article
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Identifying Origin of Replication (ORI) sites in genomic sequence using Python-based programming and Motif analysis in Bioinformatics
Abstract: ORI sites serve a critical function in DNA replication serving as the beginning point of the process. Identifying the spots appropriately means a lot and is important for the biologists working in the lab. Detecting the ORI is not only vital for the detection of replication sites but is also important in numerous biological processes. In this study, we offer a unique approach employing Python-based motif analysis to discover the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 22–33 Read article
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Photochemically Assisted LC–MS Method Development and Validation for Stability-Indicating Determination of Glasdegib in Rat Plasma
Abstract: A simple, precise, and cost-effective LC–MS method was successfully developed for the determination of Glasdegib in rat plasma. The method optimization was carried out by systematically varying key chromatographic parameters, including flow rate, injection volume, analyte concentration, and mobile phase composition, to achieve optimal sensitivity and resolution. A C18 Hypersil BDS column (150 mm × 4.6 mm, 3.5 µm particle size) was used for chromatographic separation, offering effective peak shape …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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Face Detection and Recognition Using MTCNN and FaceNet
Abstract: Face detection and face recognition are major tasks in the field of computer vision with several real-world applications and many products being developed in the same field. This study gives a detailed implementation of the product that is developed for accurate detection and recognition of faces along with audio output of the face detected. This development would act as a base for a few future products that can be developed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 132–140 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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Refining Retinal Layer Segmentation in OCT Imaging with Advanced Techniques and Clinical Applications
Abstract: Segmenting retinal layers from Optical Coherence Tomography (OCT) pictures entails locating and separating different retinal layers to offer comprehensive anatomical and pathological information. Age-related macular degeneration, diabetic retinopathy, and glaucoma are among the retinal illnesses for which this procedure is crucial for diagnosis and follow-up. By utilizing preprocessing techniques to improve image quality and applying advanced algorithms—such as intensity-based, gradient-based, and texture-based methods—alongside deep learning approaches, clinicians can accurately measure …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 01–06 Read article
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Robustness of Deepfake Detection Systems Against Adversarial Attacks
Abstract: This paper explores a deep learning system to detect deepfake videos, a common type of fake media. With the use of sophisticated methods such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), our system can reliably discern between authentic and altered videos. It analyzes both the images and the audio in videos to find signs of deepfake manipulation. We process video frames and audio, extract features with CNNs …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Essential Self-Breast Examination for Both Men and Women
Abstract: Breast self-examination stands as a crucial and foundational technique for the early detection of irregularities within the breast tissue, including both the breast itself and the nipple. This method is accessible and relevant to individuals of all genders, involving fundamental principles of observation and palpation. Those well-versed in breast self-examination possess the knowledge to guide others in this practice, which can lead to early intervention and, ultimately, the prevention of …
Published in International Journal of Midwifery Nursing And Practices · Vol. 1, Issue 2, 2023 · pp. 19–23 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 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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Gravitational Wave Astronomy (2015–2026): From Historic Discoveries to Quantum Detection Frontiers
Abstract: Since the landmark detection of GW150914 by the LIGO Scientific Collaboration in 2015, gravitational wave (GW) astronomy has transitioned from a theoretical frontier to a robust observational science. This breakthrough confirmed a major prediction of General Relativity and inaugurated an entirely new method for observing the universe. Over the past decade, continuous upgrades to ground-based interferometers such as LIGO, Virgo Collaboration, and KAGRA have dramatically improved detector sensitivity, enabling the …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 1–5 Read article