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13 results for “Feature Descriptors”
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Research ArticleOpen accessPhrase in the titleA NEW APPROACH OF LOCAL FEATURE DESCRIPTORS USING MOMENT INVARIANTSLee-Yeng Ong, Siong-Hoe Lau, Voon-Chet KooMoment invariants have been widely introduced in recognizing planar objects for a few decades. This is due the robustness of moment function in distinguishing the original identity of object under various two Dimensional (2D) transformations. A set of moments computed from a planar images, represents the global description of an object's shape and geometrical features of an image. Since global … …Journal of Computer Science, Vol. 10, Issue 12 · 29 Dec 2014 · 7,954 accessesView PDFCite
Research ArticleOpen accessIn the keywordsVehicle Identification using Fuzzy Adaline Neural NetworkGokul Murugesan, Shriram K. Vasudevan, Sivaraman Ramachandran et al.Video surveillance is an important aspect in today’s world, where a particular scene of area requires monitoring to avoid terrorist attacks and unauthorized entries. Vehicle recognition is an important area in object tracking and recognition. Objects may be of rigid or non-rigid in nature with varying velocity and have different features. Important features like shape, logo, color and texture are … …Journal of Computer Science, Vol. 9, Issue 6 · 6 Jun 2013 · 7,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpsilon-Insensitive Primal Loss With Support Vector Machine for Robust Cotton Leaf Disease ClassificationPavana Kumar Eramachetty Dhanajayalu, Malathi Sivasamy, Chitveli Siva Balaji YadavCotton diseases significantly reduce both yield and quality of crops, making early and accurate identification of the disease crucial for effective prevention and control. However, achieving a balance between lightweight models and precise classification of cotton diseases remains challenging. This difficulty arises primarily from the dispersed nature of disease symptoms and interference from noisy backgrounds, which complicate the detection process. … …Journal of Computer Science, Vol. 22, Issue 6 · 5 Aug 2026 · 755 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing N-linked Glycosylation Site Prediction in Human Proteins with Ensemble Stacking and Cross-ValidationMubina Malik, Jaimin UndaviaThe most frequent post-translational modification of proteins in all territories is glycosylation which impacts many biological activities. The most significant and critical of these modifications is N-linked glycosylation which is associated with various human diseases including diabetes cancer Inflammation Alzheimers and atherosclerosis. This article illustrates recent advances in knowledge of biology that are eventually targeting the computer science sector. Moreover-identification … …Journal of Computer Science, Vol. 20, Issue 12 · 20 Nov 2024 · 4,999 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of LDA, AdaBoost and Ensemble Bag Classifiers for Automatically Recognizing Nine Common Facial ExpressionsM.D. Sumithra, M. Abdul RahimanFacial expression recognition holds a prominent role in today’s digital world with more Human –Computer Interaction happening in day to day life. Successful identification of facial expressions needs extraction of descriptive attributes from the active facial patches and accurate classification. This paper is presented with the comparison of three multi class classifiers namely Linear Discriminant Analysis, AdaBoost and Ensemble bag. … …Journal of Computer Science, Vol. 14, Issue 9 · 27 Sep 2018 · 7,787 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study of Data Mining approaches for Bag of Visual Words Based Image ClassificationSahar Abd El Hameed Mokhtar, Heba Ahmed ElnemrImage classification is one of the most significant and challenging tasks in computer vision. The goal of this task is to build a system that is capable to reveal an image label within a collection of different image categories. This paper presents and discusses the application of various data mining techniques for image classification based on Bag of Visual Words … …Journal of Computer Science, Vol. 14, Issue 1 · 12 Jan 2018 · 7,983 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeast Absolute Deviation Regression and Least Squares for Modeling Retention Indices of Set Compounds Food and Pollutants of the EnvironmentFatiha Mebarki, Khadija Amirat, Salima Ali Mokhnach, Djellol MessadiConsidering the importance of the statistical analysis of regression in modeling based separately on study for Quantitative structure retention indices on Carbowax 20 M (ICw20M) and OV-101 columns (IOV-101) relationships (QSRR) are determined for 114 pyrazines. The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied. Least Absolute Deviation regression … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 5 Jun 2017 · 7,424 accessesView PDFCite
Research ArticleOpen accessIn the abstractLung Sound Classification Using Empirical Mode Decomposition and the Hjorth DescriptorAchmad Rizal, Risanuri Hidayat, Hanung Adi NugrohoLung sound is produced by the respiration process in the human respiratory tract. It contains information about the health of the respiratory organs. Lung sound is non-stationary signals and complex signals. One method for the analysis of non-stationary signals often used for the analysis of lung sounds is Empirical Mode Decomposition (EMD). EMD is used to view the Instantaneous Frequency … …American Journal of Applied Sciences, Vol. 14, Issue 1 · 27 Jan 2017 · 8,194 accessesView PDFCite
Research ArticleOpen accessIn the abstractCombining SURF and MSER along with Color Features for Image Retrieval System Based on Bag of Visual WordsHeba A. ElnemrContent-Based Image Retrieval (CBIR) has received an extensive attention from researchers due to the rapid growing and widespread of image databases. Despite the massive research efforts consumed for CBIR, the completely satisfactory results have not yet been attained. In this article, we offer a new CBIR technique that relies on extracting Speeded Up Robust Features (SURF) and Maximally Stable Extremal … …Journal of Computer Science, Vol. 12, Issue 4 · 9 May 2016 · 7,704 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVELTY APPROACH OF SPATIAL CO-OCCURRENCE AND DISCRETE SHEARLET TRANSFORM BASED TEXTURE CLASSIFICATION USING LPBOOSTING CLASSIFIERC. Vivek, S. AudithanRecently, the research towards Brodatz database for texture classification done at considerable amount of study has been published, the effective classification are vulnerable towards for training and test sets. This study presents the novel texture classification method based on feature descriptor, called spatial co-occurrence with discrete shearlet transformation through the LPboosting classification. It can be considered as a frame through … …Journal of Computer Science, Vol. 10, Issue 5 · 11 Jan 2014 · 6,602 accessesView PDFCite