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.
A new tensor dimensionality reduction algorithm, Orthogonal Tensor Marginal Fisher Analysis (OTMFA), is proposed in this paper, which finds a set of orthonormal transformation matrices based on Tensor Marginal Fisher Analysis (TMFA). The obtained orthonormal transformation matrices do not distort the metric of the original tensor space such that the manifold structure of the input tensors can be better...
In this paper we propose the Tensor Rank one Discriminant Locally Linear Embedding algorithm (TR1DLLE), which accept tensors as input for classification. TR1DLLE integrates the tensor rank one Analysis (TRIA) and a recently proposed graph embedding algorithm Discriminant Locally Linear Embedding (DLLE). The merits of TR1DLLE include: (1) representing data in their native structure without losing spatial...
In this paper, a new manifold learning algorithm called Orthogonal Discriminant Neighborhood Preserving Embedding (ODNPE) is proposed for facial expression recognition. The ODNPE pursues orthogonal projections vectors to preserve the local manifold within same classes and keep the separability between different classes. The obtained orthogonal projections vectors can keep the metric structure of the...
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.