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282 articles for “image enhancement”
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Effect of Carbon Nanotube on Mechanical Properties of Jute Fibre Reinforced Polyester Composite
Abstract: The current study studies how carbon nanotubes affect the mechanical characteristics of polyester composites reinforced with jute fiber, both treated and unprocessed. Alkali was used to cure jute textiles. Composites with treated and untreated jute fibre with 5%, 10% and 15% jute fibre loading with and without carbon nanotube were prepared using hand lay-up process. Carbon nanotubes varied from 0.2%, 0.4% and 0.6%. Tensile, flexural, and strength of impact all …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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Unravelling the Impact of AI: Insights into Pattern Recognition and Image Processing
Abstract: Apart from its academic origins, the evolution of Artificial Intelligence (AI) has emerged as a notable influence in shaping our daily experiences. Artificial intelligence, which focuses on domains such as image processing and pattern recognition, encompasses a vast array of topics, including its complex applications, obstacles, and societal repercussions. Machine Learning, Natural Language Processing, Computer Vision, Robotics, Expert Systems, Knowledge Representation, and AI Ethics are among the domains in which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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MIRDcalc & OLINDA/EXM Dosimetry Software Analysis by SPECT/CT Scan Data of Lu-177 DOTATATE Radionuclide Therapy of NET Patients
Abstract: Accurate dosimetry is essential in nuclear medicine for optimizing radionuclide therapies and ensuring patient safety. In Radiopharmaceutical dosimetry the Medical Internal Radiation Dosimetry (MIRD)Society is the pioneer in organ-level dosimetry providing the fundamental basis for commonly used clinical and research dosimetry software like MIRDOSE and OLINDA/EXM. Recently, in MIRD Pamphlet No. 28, Part 1, the MIRD committee of the Society of Nuclear Medicine and Medical Imaging presented a new Software …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 48–63 Read article
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Management of Varicose Veins: A Review of Literature
Abstract: Lower extremities venous insufficiency is a frequent disorder that can cause a variety of symptoms, such as ulceration, soreness, swelling, and bulging leg veins. Whereas there is many other treatment choices, the more recent endovascular treatments are simple, safe, rapid, and very effective at reducing symptoms. Foam sclerotherapy, thermal ablation, and mechanical chemical ablation are minimally invasive endovascular techniques commonly used in the treatment of varicose veins. This review article …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 1, 2025 · pp. 17–21 Read article
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Sustainable Advances in Oral Pathology: The Impact of Artificial Intelligence
Abstract: Oral cavity cancers constitute about 4% of all malignant neoplasms. More than 9,900 new cases are reported from the developed countries yearly, and the 5-year mortality rate is higher than 39%. In Europe, the highest rates occur in Hungary, Croatia, and other Central and Eastern European countries; high levels are also seen in India, Pakistan, and Bangladesh. The management of endosseous pathologies presents considerable challenges because they often exhibit no …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 24–27 Read article
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Impact of Hypoxia on Cardiopulmonary Adaptation in Canines: A Comprehensive Review
Abstract: Hypoxia triggers a series of cardiopulmonary responses that play an important role in oxygen delivery and the continuation of physiological activity in mammals. Canines are also a useful translational model of study to examine these adaptive responses because of their anatomical, physiological, and cardiopulmonary differences with humans. This review summarizes the experimental data of acute, subacute and chronic hypoxia in dogs with particular focus on the variations in cardiac functioning, …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 15, Issue 1, 2026 · pp. 13–24 Read article
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Artificial Intelligence in Image Recognition: Context of Machine Vision
Abstract: The machine learning discipline is as old as decades, but some problems such as image recognition, location detection, image classification, image generation, speech recognition, and natural language processing cannot be solved. Image classification studies are another basic, most classic and essential line of research in deep learning. Computer intelligent recognition of the images technology has enabled a gradual reaction (updating) to foreign measurement trends, which promotes advancement of different areas …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Optimizing the Work Environment for Interior Designers: Enhancing Creativity, Collaboration, and Well-being in Design Studios and Beyond
Abstract: In the field of interior design, the conventional office setup is no longer adequate to unleash the full creative potential of designers. This paper advocates for environments that go beyond the basic provisions of a laptop and chair, emphasizing the necessity of spaces that truly ignite creativity. By delving into the unique requirements of interior designers, this research underscores the critical importance of environments that engage the senses and facilitate …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 1–14 Read article
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Polymer-Based Medical Restraints: Advances in Polymer Chemistry for Enhanced Patient Safety
Abstract: Medical restraints play a crucial role in ensuring patient and staff safety during medical procedures, particularly when dealing with individuals who may be at risk of self-harm or unintentional movement. Traditional restraints, often made from rigid materials or fabric straps, present several challenges, including patient discomfort, pressure injuries, and incompatibility with advanced medical imaging techniques such as MRI and CT scans. Moreover, traditional materials may deteriorate over time, diminishing their …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 153–157 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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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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The Effect of Packaging Design Elements on Purchase Intention of Junk Food Among College Students
Abstract: This research investigates the impact of packaging design elements on the purchase intention of junk food among college students. Recognizing the influence of visual appeal on consumer behavior, particularly within young adult demographics, this study aims to identify which specific packaging elements, such as color, imagery, typography, and branding, resonate most with college students when choosing junk food. A descriptive survey method was used, targeting students in Delhi NCR, with …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 14, Issue 3, 2024 · pp. 39–47 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 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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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article