Real membership authentication applications require machines to learn from stream data while making a decision as accurately as possible whenever the authentication is needed. To achieve that, we proposed a novel algorithm which authenticated membership by a one-pass incremental principle component analysis(IPCA) learning. It is demonstrated that the proposed algorithm involves an useful increm...

The spatial prepositions in and on apply to a wide range of containment and support relations, making exhaustive definitions difficult. Theories differ in whether they endorse geometric or functional properties and how these properties are related to meaning and use. This study directly examines the roles of geometric and functional information in adults’ and children’s use of in and on by deve...

We propose a spectral technique for analysing intermediate feature space of multiple classifier decisions, which enables a separable subset of patterns to be extracted. The method is applied to finding a set of patterns that are inconsistently classified, a random subset of which is left out of the training set of each expert in a multiple classifier framework.

When considering the prediction of a structural class for a protein as a classification problem, usually a classifier is based on a feature vector x ∈ R, where the features represent certain attributes of the primary sequence or derived properties (e.g., the predicted secondary structure) of a given protein. Since the structure of a protein (i.e., its native conformation) is stable only under s...

Content-based queries in multimedia sequence databases where information is sequential is a tough issue, especially when dealing with large scale applications. One of the key points is similarity estimation between a query sequence and elements of the database. In this paper, we investigate two ways to compare multimedia sequences, one – that comes from the literature – being computed in the fe...

Capturing place semantics is critical for enabling location-based applications. Techniques for assigning semantic labels (e.g., “bar” or “office”) to unlabeled places mainly resort to mining user activity logs by exploiting visiting patterns. However, existing approaches focus on inferring place labels with a static user activity dataset, and ignore the visiting pattern dynamics in user activit...

ÐWe studied a number of measures that characterize the difficulty of a classification problem, focusing on the geometrical complexity of the class boundary. We compared a set of real-world problems to random labelings of points and found that real problems contain structures in this measurement space that are significantly different from the random sets. Distributions of problems in this space ...

In this paper, we proposed a new fast technique of face authentication based on extraction of a simple Statistical features derived from the image of face. Once the feature vector is extracted, we comparing it with the feature vector of face which is authenticated, and we calculated the error rates in the two sets of validation and test for the data base XM2VTS

This paper presents a new approach to synthesize face images under different pose changes from a single input image. The approach is based on two observations: 1. face images from a single person under different poses could be mapped to a smooth manifold in a unified feature space. 2. the manifolds from different faces are separated from each other by their similarities. The new manifold estima...

As an interesting and emerging topic, zero-shot recognition (ZSR) makes it possible to train a recognition model by specifying the category’s attributes when there are no labeled exemplars available. The fundamental idea for ZSR is to transfer knowledge from the abundant labeled data in different but related source classes via the class attributes. Conventional ZSR approaches adopt a two-step s...