Facial recognition is a challenging issue in pattern recognition arising from the need for high security systems capable of overcoming the variability of the acquisition environment such as illumination, pose or
David L. IiElliott D. ReitzDennis A. TillotsonUSUS20040042650 * 2002年8月30日 2004年3月4日 Lockheed Martin Corporation Binary optical neural network classifiers for pattern recognitionUS20040042650 2002年8月30日 2004年3月4日 Lockheed Martin Corporation Binary optical neural network classifiers for ...
J. G. Lisboa, "Translation, rotation and scale in- variant pattern recognition by high-order neural networks and moment classifiers," IEEE Trans. Neural Networks, vol. 3, pp. 241-251, 1992.S. J. Perantonis and P. J. G. Lisboa, "Translation, rotation, and scale invariant pattern ...
K nearest neighbor classifier (K-NN) is widely discussed and applied in pattern recognition and machine learning, however, as a similar lazy classifier using local information for recognizing a new test, neighborhood classifier, few literatures are reported on. In this paper, we introduce neighborhoo...
Recent research has linked backpropagation (BP) and radial basis function (RBF) network classifiers, trained by minimizing the standard mean square error (MSE), to two main topics in statistical pattern recognition (SPR), namely the Bayes decision theory and discriminant analysis. However, so far...
Multipleclassifiersensemble is an effective method to solve complex classification problems in pattern recognition field. 多分类器组合是解决复杂模式识别问题的有效办法. 互联网 When used properly,classifiersmake the accuracy, sharpness and vividness of language and vice versa. ...
(2019). Evaluating Restrictions in Pattern Based Classifiers. In: Nyström, I., Hernández Heredia, Y., Milián Núñez, V. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2019. Lecture Notes in Computer Science(), vol 11896. Springer, Cham....
The on-line multiclassifier optimization approach is applicable to any pattern recognition problem. The proposed method needs neither a priori distributions nor pre-estimated weights, and does not make use of any consideration about training/testing matching conditions. Results with Yoho database show ...
Therefore, in machine learning and pattern recognition, the preprocessing generally starts by extracting a vector of features that help the system recognize the image [20]. Features could be points, edges, and directions of certain points in an object, such as the direction of hand bones [20]...
A classifier reads the data in a data store. If it recognizes the format of the data, it generates a schema. The classifier also returns a certainty number to indicate how certain the format recognition was. AWS Glue provides a set of built-in classifiers, but you can also create custom ...