نتایج جستجو برای: multilayer perceptron
تعداد نتایج: 23424 فیلتر نتایج به سال:
This work presents a constructive method to train the multilayer perceptron layer after layer successively and to accomplish the kernel used in the support vector machine. Data in different classes will be trained to map to distant points in each layer. This will ease the mapping of the next layer. A perfect mapping kernel can be accomplished successively. Those distant mapped points can be dis...
Label Ranking problems are receiving increasing attention in machine learning. The goal is to predict not just a single value from a finite set of labels, but rather the permutation of that set that applies to a new example (e.g., the ranking of a set of financial analysts in terms of the quality of their recommendations). In this paper, we adapt a multilayer perceptron algorithm for label rank...
In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multilayer Perceptrons are one of the most successful non-linear regression tool but they are unfortunately restricted to inputs and outputs that belong to a normed vector space. In this chapter, we propose a general recoding...
We propose a text scanner, which detects wide text strings in a sequence of scene images. For scene text detection, we use a multiple-CAMShift algorithm on a text probability image produced by a multi-layer perceptron. To provide enhanced resolution of the extracted text images, we perform the text detection process after generating a mosaic image in a fast and robust image registration
The aim of this paper is to examine a multiclassifier approach to the classification of the lung nodules in X-ray chest radiographs. The approach investigated here is based on an image region-based classification whose output is the information of the presence or absence of a nodule in an image region. The classification was made, essentially, in two steps: firstly, a set of rotation invariant ...
Classification of imbalanced data is pervasive but it is a difficult problem to solve. In order to improve the classification of imbalanced data, this letter proposes a new error function for the error backpropagation algorithm of multilayer perceptrons. The error function intensifies weight-updating for the minority class and weakens weight-updating for the majority class. We verify the effect...
For technical speech recognition systems as well as for humans it has been shown that the combination of acoustic and optic information can enhance speech recognition performance. But it still remains an open question, at which stage of processing the two information channels should be combined. In this paper we systematically investigate this problem by means of a neural speech recognition sys...
In the eighties the problem of the lack of an efficient algorithm to train multilayer Rosenblatt perceptrons was solved by sigmoidal neural networks and backpropagation. But should we still try to find an efficient algorithm to train multilayer hardlimit neuronal networks, a task known as a NP-Complete problem? In this work we show that this would not be a waste of time by means of a counter ex...
Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-...
In this paper, a multilayer perceptron guided encryption/decryption (STMLP) in wireless communication has been proposed for exchange of data/information. Multilayer perceptron transmitting systems at both ends generate an identical output bit and the network are trained based on the output which is used to synchronize the network at both ends and thus forms a secret-key at end of synchronizatio...
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