Research ArticleOpen accessAll words, across the recordPolar Disentangled Non-Local Convolutional Neural Network for Skin Cancer Classification Using Dermoscopy ImagesUsha Thirugnanam, Nalini JosephSkin cancer classification is the process of identifying and categorizing various types of skin lesions into cancerous and non-cancerous. This process is performed to achieve accurate detection, which minimizes the risk of severe health complications. However, classifying the severity of skin lesion images is a difficult task because of subtle and overlapping visual patterns, which could lead to inaccurate performance. … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,207 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordBenchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease DetectionPrince Daughin Ngqabutho NcubeSorghum is a climate-resilient cereal crop central to food and livelihood security across Southern Africa, yet its productivity is frequently reduced by foliar diseases that smallholder farmers struggle to diagnose reliably in the field. While deep learning has demonstrated strong potential for automated plant disease identification, sorghum remains underrepresented in the literature, and no prior study has provided a comprehensive, … …Journal of Computer Science, Vol. 22, Issue 10 · 29 Sep 2026 · 535 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAn Effective Method for the Recognition and Verification of Bangladeshi Vehicle Digital Number PlatesMd. Ashraful Islam, Ahsan HabibIn this study, an effective and automatic technique has been proposed to detect, recognize and verify Bangladeshi number plates. There are four steps in the proposed method: Pre-processing, extraction and segmentation, recognition and verification of the number plate. Image contrast-enhancing and tilt correction techniques are used in the proposed method. Different techniques like edge detection, morphological operations, bounding box method … …Journal of Computer Science, Vol. 17, Issue 11 · 20 Nov 2021 · 6,508 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordContent Based Image Retrieval of Ultrasound Liver Diseases Based on Hybrid ApproachR. Suganya, S. RajaramProblem statement: In the past few years, immense improvement was obtained in the field of Content-Based Image Retrieval (CBIR). Nevertheless, existing systems still fail when applied to medical image databases. Simple feature-extraction algorithms that operate on the entire image for characterization of color, texture, or shape cannot be related to the descriptive semantics of medical knowledge that is extracted from … …American Journal of Applied Sciences, Vol. 9, Issue 6 · 24 Mar 2012 · 7,643 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA New Discussion of Different Noises and FiltersP.N. Sundararajan, S. Sasi KumarIn digital image processing, noise acquisition and noise removal is required to enhance the quality of an image and during transmission variety of noise that affects the quality of the image. The major intension of filtering or de-noising the image is to reconstruct the detail of master image as much as possible. The metrics of the image noise removal trouble … …American Journal of Applied Sciences, Vol. 11, Issue 12 · 3 Jan 2015 · 5,973 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Novel Approach to Classify Noises in Images Using Artificial Neural NetworkT. Santhanam, S. RadhikaProblem statement: Noise identification is predominant in any digital image processing algorithms, which helps in identifying the filters to smooth the image for further processing. Approach: An Artificial Neural Network (ANN) based approach was proposed for noise identification. The suggested technique involved seclusion of the noise samples and extracts their statistical features, which was then applied to a neural network … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,190 accessesView PDFCite