The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
For hyperspectral imagery (HSI) classification, many works have shown the effectiveness of the spectral–spatial method. However, some previous works using neighboring information assumed that all neighboring pixels make an equal contribution to the central pixel, which is unreasonable for heterogeneous pixels, especially near the boundary of a region. In this letter, a nonlocal self-similarity based...
For Electrotechnics involves complex content, it contains lots of knowledge, this paper proposes some reformation ways and teaching methods of the Electrotechnics course. In order to stimulate students' interest and initiative to improve the teaching quality of Electrotechnics course, we raised to combine the theory and practice, carry out various teaching methods, and use various means to check students'...
Statistic classification of hyperspectral data is a great challenge because of its large number of spectral channels, especially when the labeled training samples are relatively few. Most of the classification methods require using a large number of training samples, but in remote sensing situations, identifying and labeling samples are extremely difficult and expensive. A sparse representation classification...
The standard support vector machine (SVM) is a common method of machine learning, the parameters selection of SVM affects the machine learning ability directly. At present, the research on the choice of SVM parameters is still no uniform approach. In order to avoid the difficult problem of selecting parameters, this paper used a deformed SVM, that is, v-SVM, selected parameters of v-SVM by particle...
To solve the problem that the performance of speech recognition systems declines in the noisy environment, this paper used the linear predictive Mel frequency cepstrum coefficients according with human hearings characteristic as speech feature parameters, adopted two recognition machines, the support vector machine and the wavelet neural network, realized respectively a speech recognition system of...
To improve the generalization ability of the machine learning and solve the problem that recognition rates of the speech recognition system become worse in the noisy environment, a modified Gaussian kernel function which may pay attention to the similar degree between sample space and feature space is proposed. In this paper, used the modified Gaussian kernel support vector machine to a speech recognition...
To improve the learning and generalization ability of the machine-learning model, a new compound kernel that may pay attention to the similar degree between sample space and feature space is proposed. In this paper, used the new compound kernel support vector machine to a speech recognition system for Chinese isolated words, non-specific person and middle glossary quantity, and compared the speech...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.