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56 articles for “recognition algorithms”
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Research ArticleOpen accessIn the abstractEnhanced Support Vector Machine based on Metaheuristic Search for Multiclass ProblemsAbdullah Saeed Ghareb, Mohammed Hamid Afif, Abdel-Rahman Hedar et al.Machine learning is an important field of artificial intelligent researches and it highly growing for real intelligent applications systems that relate brain computer interface to human brain activities. Support Vector Machine (SVM) is a popular machine learning approach, which can be used for pattern recognition, prediction and classification with many diverse applications. However, the SVM has many parameters, which have … …Journal of Computer Science, Vol. 16, Issue 7 · 9 Jul 2020 · 6,911 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Flexible, Real-Time Algorithm for Simulating Correlated Random Fields and Its PropertiesMichael A. Kouritzin, Fraser Newton, Biao WuContemporary real-time problems like CAPTCHA generation and optical character recognition can be solved effectively using correlated random fields. These random fields should be produced on a graph in order that problems of any dimension and shape can be handled. However, traditional solutions are often too slow, inaccurate or both. Herein, the Quick Simulation Random Field algorithm to produce correlated random … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractA HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATIONMutasem K. AlsmadiImage processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI). A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 10 Sep 2014 · 8,081 accessesView PDFCite
Research ArticleOpen accessIn the abstractREMOVAL OF HIGH DENSITY IMPULSE NOISE USING MORPHOLOGICAL BASED ADAPTIVE UNSYMMETRICAL TRIMMED MID-POINT FILTERS. Saravanakumar, A. Ebenezer Jeyakumar, K. N. VijeyakumarA Morphological based Adaptive Unsymmetrical Trimmed Mid-Point Filter (MAUTMPF) for the restoration of gray scale images corrupted by salt and pepper noise for varying noise densities is proposed in this study. Images corrupted by impulsive noise severely hinder subsequent image processing tasks, such as edge detection, image segmentation, object recognition, etc. Therefore, it is absolutely essential to restore the original … …Journal of Computer Science, Vol. 10, Issue 7 · 17 Jun 2014 · 6,547 accessesView PDFCite
Research ArticleOpen accessIn the abstractCOMBINATION OF DIFFERENCE SUBSPACE AND OPPURTUNISTIC CLUSTERING ON HIGH DIMENSIONAL DATAM. Ravichandran, A. ShanmugamClustering is recognized as sigificant technique for analysing data and concentric effort has been taken in different domains comprises of recognition of pattern, statistical analysis and data mining for decades. Subspace clustering is developed from the group of cluster objects from all subspaces of a dataset. During clustering of objects involing higher dimension, the accuracy and effectiveness of traditional clustering … …Journal of Computer Science, Vol. 10, Issue 8 · 11 Mar 2014 · 6,359 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Independent Rough Set Approach Hybrid with Artificial Bee Colony Algorithm for Dimensionality ReductionNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Dimensionality reduction is viewed as an important pre-processing step for pattern recognition and data mining. As the classical rough set model considers the entire attribute set as a whole to find the subset, comparing all possible combinations of sets of attributes is difficult. Approach: In this study, we have introduced an improved Rough Set-based Attribute Reduction (RSAR) namely … …American Journal of Applied Sciences, Vol. 8, Issue 3 · 25 Mar 2011 · 8,342 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Biometrics Based on Principal Component Analysis and Linear Discriminant AnalysisLih-Heng Chan, Sh-Hussain Salleh, Chee-Ming TingProblem statement: In facial biometrics, face features are used as the required human traits for automatic recognition. Feature extracted from face images are significant for face biometrics system performance. Approach: In this thesis, a framework of facial biometric was designed based on two subspace methods i.e., Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). First, PCA is used for … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,668 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Set of RST Moment InvariantsKhalid M. HosnyMoment invariants are widely used in image processing, pattern recognition and computer vision. Several methods and algorithms have been proposed for fast and efficient calculation of moment's invariants where numerical approximation errors are involved in most of these methods. In this paper, an optimized set of moment invariants with respect to rotation, scaling and translation is presented. An accurate method … …American Journal of Applied Sciences, Vol. 5, Issue 6 · 30 Jun 2008 · 7,070 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Performance of Maximum Likelihood, Spectral Angle Mapper, Neural Network and Decision Tree Classifiers in Hyperspectral Image AnalysisHelmi Zulhaidi Mohd Shafri, Affendi Suhaili, Shattri MansorSeveral classification algorithms for pattern recognition had been tested in the mapping of tropical forest cover using airborne hyperspectral data. Results from the use of Maximum Likelihood (ML), Spectral Angle Mapper (SAM), Artificial Neural Network (ANN) and Decision Tree (DT) classifiers were compared and evaluated. It was found that ML performed the best followed by ANN, DT and SAM with … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 142,423 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordArtificial Neural Networks Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemSaleh Mufleh Al-Saqer, Ghulam Mubashar HassanProblem statement: The most dangerous insect for the existence of palm trees in entire world is Red Palm Weevil (scientifically named as Rynchophorus Ferrugineous, Oliveir). The proposed research is conducted to develop an identification system for Automated Wireless Red Palm Weevil Detection and exterminated. The core idea of the proposed research is to develop software that can utilize image processing … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 3 · 4 Aug 2011 · 9,190 accessesView PDFCite