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OCR Feature of PDFelement Pro. ... Support 23 languages: English, German, French, Italian, Portuguese, Spanish, Japanese, and Chinese Traditional etc. ... After enabling the OCR feature in PDFelement Pro, all features will be applicable to scanned PDFs. The application of the kernel of Equation (21.45) results in a multivector classifier based on a multivector polynomial of degree p. An SMVM with kernels according to Equation (21.46), constitutes a Gaussian radial basis function multivector classifier. The reader can see that by using the SMVM approach we can straightforwardly generate multivector RBF networks, avoiding the complications of training that are encountered in the use of classical RBF networks. The number of the centers Ns = m 2n m2n -dimensional multivectors), the centers themselves si i = 1 Ns , the weights i=1 Ns and the threshold b are all produced automatically by the SMVM training. This i is an important contribution to the field, because in earlier work [16,21], we simply used extensions of the real-valued networks RBFs for the so-called geometric RBF networks with classical training methods. We believe that the use of RBF SMVM presents a promising neurocomputing tool for various applications of data coded in geometric algebra. In the case of two-layer networks (Equation (21.47)), the first layer is composed of Ns1 sets of weights, with each set consisting of the dimension of the data d = m 2n and m2n -dimensional multivectors, whereas the second layer is composed of Ns2 weights (the i ). In this way, according to Cybenko s theorem [4], an evaluation simply requires the consideration of the weighted sum of sigmoid functions, evaluated on inner products of test data with the multivector support vectors. Using our approach, we can see that the architecture (Ns2 weights) is found automatically by the SMVM. ocr software free download softonic PDF to text, how to convert a PDF to text | Adobe Acrobat DC
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