首页|New Support Vector Machines Findings from Uttaranchal University Described (Impr oving Offline Gurmukhi Character Recognition: a Comparative Study of Feature Sel ection Techniques)
New Support Vector Machines Findings from Uttaranchal University Described (Impr oving Offline Gurmukhi Character Recognition: a Comparative Study of Feature Sel ection Techniques)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Su pport Vector Machines. According to newsoriginating from Dehradun, India, by Ne wsRx correspondents, research stated, “In this study, we introduceand assess a novel feature extraction technique that analyzes the extent of character image b oundariesto enhance recognition accuracy. This method is evaluated in conjuncti on with Nearest Neighbors (NN)and Support Vector Machine (SVM) classifiers, and compared against various feature selection methodsincluding Consistency Based Analysis (CBA), Correlation Feature Set (CFS), Chi-Squared Attribute (CSA),Inde pendent Component Analysis (ICA), Latent Semantic Analysis (LSA), Principal Comp onent Analysis(PCA), and Random Projection (RP).”
DehradunIndiaAsiaEmerging Technolo giesMachine LearningSupport Vector MachinesVector MachinesUttaranchal Un iversity
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