首页|Study Findings from Xidian University Provide New Insights into Support Vector M achines (Small Target Detection In Sea Clutter By Weighted Biased Soft-margin Sv m Algorithm In Feature Spaces)
Study Findings from Xidian University Provide New Insights into Support Vector M achines (Small Target Detection In Sea Clutter By Weighted Biased Soft-margin Sv m Algorithm In Feature Spaces)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Machine Learning - Suppo rt Vector Machines have been published. According to news reporting originating in Xi’an, People’s Republic of China, by NewsRx journalists, research stated, “S ea-surface small target detection in high-resolution sea clutter is always an in tractable problem. Feature-based detection in multidimensional feature spaces is recognized to be an effective way, and therein, learning algorithms with contro llable false alarm rate play an important role.”
Xi’anPeople’s Republic of ChinaAsiaAlgorithmsMachine LearningSupport Vector MachinesXidian University
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