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Method Classification Recognition rate % MMD Unsupervised 94.4 SVM by charac.
We achieve promising performance in vessel classification, recognition, and retrieval.
SVM is a popular tool for machine learning tasks involving classification, recognition, or detection.
Many decades of active research has been done on shape representation for object classification, recognition, and detection.
Support Vector Machine (SVM) has become an increasing popular tool for machine learning tasks involving classification, recognition, or detection.
influence of different length of the feature vector on the computational time (complexity) of the phases: GMM creation, training, and classification (recognition); 5.
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The combinatorial signals pattern emerging form the ensemble of receptors is the key for odor classification, identification, and recognition [2].
Support vector machines (SVMs) modeling technique has been widely applied in text classification, image recognition, voice recognition in machine learning.
Finally, extensive comparison experiments on scene categorization, object classification, action recognition and face recognition clearly verify the classification performance of the proposed algorithm.
Then, we develop target type classification and recognition algorithm based on machine learning techniques.
An improved support vector machine (SVM) classifier is developed to perform target types classification and recognition.
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