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176 results for “image classification”
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Research ArticleOpen accessEvery word in the titleEffectual Deep Learning Based Digital Image Forgery Detection Model Using Ameliorate CNN, VGG 16 and VGG 19 for Copy Move and Image Splicing Classification With Enhanced PerformancePreeti Dhiman, Usha ChauhanIn this research, a pioneer passive approach for detecting and localizing tampering in images is proposed. In the past, image forgeries have created a huge impact in the world. Developments of various image processing technologies made it easier to tamper images with the objective to cover up or hide a significant feature in an image. In some situation, such as … …Journal of Computer Science, Vol. 22, Issue 10 · 3 Oct 2026 · 568 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDesign an Advance Computer-Aided Tool for Image Authentication and ClassificationRozita Teymourzadeh, Amirize Alpha Laadi, Yazan Samir Algnabi et al.Over the years, advancements in the fields of digital image processing and artificial intelligence have been applied in solving many real-life problems. This could be seen in facial image recognition for security systems, identity registrations. Hence a bottleneck of identity registration is image processing. These are carried out in form of image preprocessing, image region extraction by cropping, feature extraction … …American Journal of Applied Sciences, Vol. 10, Issue 7 · 24 Jun 2013 · 6,561 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Integrated Disease Progression Model to Analyze Electronic Health Records With Multimodal Datasets Using Deep Learning TechniquesThulaganyo Dimakatso, Venumadhav Kuthadi, Rajalakshmi Selvaraj, Othapile DinakenyaneIn contemporary clinical environments, precisely simulating the emergence of disease is an intricate task owing to heterogeneously derived data and variability in the record of diagnoses. The research presents a stable classification model that integrates image data with formalized patient data to track patterns in disease through various stages. The suggested approach combines a multi-stage analytical methodology that includes systematic … …Journal of Computer Science, Vol. 22, Issue 2 · 19 Feb 2026 · 1,678 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOptiCNN: Local thresholding segmentation and CNN with SVM Approach for Diabetic Retinopathy Detection and Classification of Fundus ImagesAnju Mishra, Mrinal Pandey, Laxman SinghDiabetic Retinopathy (DR) is a progressive eye disease that can lead to vision loss and blindness if left untreated. Ophthalmologists diagnose DR using medical imaging modalities such as fundus photography and optical coherence tomography (OCT); however, manual interpretation of these images is time-consuming and subject to inter-observer variability. While DR is irreversible, vision loss can be prevented through early detection … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,153 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparison of Classification Techniques on Fused Optical and SAR Images for Shoreline Extraction: A Case Study at Northeast Coast of Peninsular MalaysiaSyaifulnizam Abd Manaf, Norwati Mustapha, Md Nasir Sulaiman et al.Shoreline is a very important element to identify exact boundary at the coastal areas of a country. However, in order to identify land-water boundary for a large region using traditional ground survey technique is very time consuming. Alternatively, shoreline can be extracted by using satellite images that minimizes the mapping errors. The trend of extracting shoreline has been shifted from … …Journal of Computer Science, Vol. 12, Issue 8 · 27 Oct 2016 · 7,708 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFEATURE DIMENSION REDUCTION FOR EFFICIENT MEDICAL IMAGE RETRIEVAL SYSTEM USING UNIFIED FRAMEWORKYogapriya Jaganathan, Ila VennilaFeature dimensionality reduction problem is a major issue in Content Based Medical Image Retrieval (CBMIR) for the effective management of medical images with the support of visual features for the purpose of diagnosis and educational research field. The proposed CBMIR is used a unified approach based on extraction of visual features, optimized feature selection, classification of optimized features and similarity … …Journal of Computer Science, Vol. 9, Issue 11 · 24 Sep 2013 · 6,982 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn integrated Framework Based on Texture Features, Cuckoo Search and Relevance Vector Machine for Medical Image Retrieval SystemYogapriya Jaganathan, Ila VennilaAs medical images are widely used in healthcare applications, Content Based Medical Image Retrieval (CBMIR) system is needed for physicians to convey effective decisions to patients and for medical research students to learn imaging characteristics for their extensive research based on visual features. However the performance of the retrieval is restricted due to high feature dimensionality of visual features. To … …American Journal of Applied Sciences, Vol. 10, Issue 11 · 24 Sep 2013 · 6,878 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFeature Extraction and Classification of Blood Cells Using Artificial Neural NetworkMagudeeswaran Veluchamy, Karthikeyan Perumal, Thirumurugan PonuchamyProblem statement: One method of evaluating the clinical status is counting of cell types based on features that it contains. There is a need for a rapid, reproducible method, superior to human inspection and for the classification of cells. For solving these problems, quantitative digital-image analysis is applied and a novel method for classifications of affected blood cells from normal … …American Journal of Applied Sciences, Vol. 9, Issue 5 · 18 Feb 2012 · 8,156 accessesView PDFCite
Research ArticleOpen accessIn the keywordsContent Based Image Retrieval using Novel Gaussian Fuzzy Feed Forward-Neural NetworkC. Ramesh Babu Durai, V. DuraisamyProblem statement: With extensive digitization of images, diagrams and paintings, traditional keyword based search has been found to be inefficient for retrieval of the required data. Content-Based Image Retrieval (CBIR) system responds to image queries as input and relies on image content, using techniques from computer vision and image processing to interpret and understand it, while using techniques from information … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 7,326 accessesView PDFCite
Research ArticleOpen accessIn the keywordsExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite