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Research ArticleOpen accessIn the abstractNasal Administration of Quercetin Liposomes Improves Memory Impairment and Neurodegeneration in Animal Model of Alzheimer's DiseaseTerdthai Tong-un, Supaporn Muchimapura, Jintanaporn Wattanathorn, Wathita PhachonpaiProblem statement: At present, the development of protective strategy against Alzheimer’s Disease (AD) is increasing its importance due to the high prevalence of AD, a limitation of therapeutic efficacy and its high impacts on economic and social aspects. The development of the preventive and therapeutic strategy to protect against the path physiology induced by free radicals in AD from antioxidant … …American Journal of Agricultural and Biological Sciences, Vol. 5, Issue 3 · 30 Sep 2010 · 7,743 accessesView PDFCite
Literature ReviewOpen accessIn the abstractEfficient Morphometric Techniques in Alzheimer’s Disease Detection: Survey and ToolsVinutha N., P. Deepa Shenoy, K.R. VenugopalThe development of advance techniques in the multiple fields such as image processing, data mining and machine learning are required for the early detection of Alzheimer’s Disease (AD) and to prevent the progression of the disease to the later stages. The longitudinal and cross sectional images of elderly subjects were obtained from the standard datasets like ADNI, OASIS, MIRIAD and … …Neuroscience International, Vol. 7, Issue 2 · 4 Oct 2017 · 8,450 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffects of Quercetin Encapsulated Liposomes via Nasal Administration: A Novel Cognitive EnhancerTerdthai Tong-un, Supaporn Muchimapura, Wathita Phachonpai, Jintanaporn WattanathornProblem statement: Demand for cognitive-enhancing drugs is growing. Numerous medicinal plants possessing antioxidant activity have received much attention as food supplement to improve cognitive function. Quercetin is a potent free radical scavenger and antioxidant. However, the limitations of quercetin: Rapidly metabolized is an obstacle to its use for a cognitive enhancer. In addition, the burden of blood brain barrier can … …American Journal of Applied Sciences, Vol. 7, Issue 7 · 31 Jul 2010 · 7,498 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Use of Neural Network to Recognize the Parts of the Computer MotherboardAbbas M. Ali, S. D. Gore, Musaab AL-SarierahThis study suggests a new approach of learning which utilizes the techniques of computer vision to recognize the parts inside the motherboard. The main thrust is to identify different parts of the motherboard using a Hopfield Neural Network. The outcome of the net is compared with the objects stored in the database. The proposed scheme is implemented using bottom -up … …Journal of Computer Science, Vol. 1, Issue 4 · 31 Dec 2005 · 6,865 accessesView PDFCite
Research ArticleOpen accessIn the abstractFLANN Detector Based Filtering of Images Corrupted by Impulse NoiseBanshidhar Majhi, Mowafak FathiWe present a novel non-linear scheme for image restoration based on neuro-detector using Functional Link Artificial Neural Network (FLANN) followed by an improved spatial filter. The method is applied to images corrupted by impulse noise with varying strengths and different noise probability. The neural detector is based on the concept of training or learning by examples. When trained properly, the … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 7,237 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,107 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordTransforming Retinal Diagnostics: Advanced Detection of Diabetic Retinopathy Using Vision Transformers and Capsule NetworksVishal Sharma, Rishu, Vinay Kukreja et al.Diabetic Retinopathy (DR), nowadays is one of the leading causes of blindness worldwide, it is a severe complication of diabetes mellitus that affects the retina blood vessels. Accurate diagnosis depends on early detection of DR. The study aims to develop a hybrid model that is the combination of a Vision Transformer and Capsule Network (ViT-CapsNet) to classify the DR at … …Journal of Computer Science, Vol. 21, Issue 2 · 14 Jan 2025 · 6,755 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAutomated Medical Image Captioning with Soft Attention-Based LSTM Model Utilizing YOLOv4 AlgorithmPaspula Ravinder, Saravanan SrinivasanThe medical image captioning field is one of theprominent fields nowadays. The interpretation and captioning of medical imagescan be a time-consuming and costly process, often requiring expert support. Thegrowing volume of medical images makes it challenging for radiologists tohandle their workload alone. However, addressing the issues of high cost andtime can be achieved by automating the process of medical image … …Journal of Computer Science, Vol. 20, Issue 1 · 16 Dec 2023 · 6,651 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,342 accessesView PDFCite