ABTRACT A novel integrated approach for resolving the effect of illumination changes on face recognition is proposed. This face recognition system comprises feature extraction, feature selection and recognition. For feature extraction, a normal shrink filter in NSCT domain denoising technique is applied which produces illuminant invariant for the given image. In the second phase, to capture the...

Convolutional Neural Networks (CNNs) have been shown their performance in speech recognition systems for extracting features, and also acoustic modeling. In addition, CNNs have been used for robust speech recognition and competitive results have been reported. Convolutive Bottleneck Network (CBN) is a kind of CNNs which has a bottleneck layer among its fully connected layers. The bottleneck fea...

Social species that maintain individualised relationships with certain others despite continuous changes in age, reproductive status and dominance rank between group members ought to be capable of individual recognition. Tests of "true" individual recognition, where an individual recognises unique features of another, are rare, however. Often kinship and/or familiarity suffice to explain dyadic...

Comparative study of the recognition of nonsemantic geometrical figures by the human subjects and ART neural network was carried out. The results of computer simulation experiments with ART neural network showed well correspondence with the psychophysical data on the recognition of different complexity visual patterns: in both cases the patterns of medium complexity were recognized with the hig...

In pattern recognition applications with high number of input features and insufficient number of samples, the curse of dimensionality can be overcome by extracting features from smaller feature subsets. The domain knowledge, for example, can be used to group some of the features together, which are also known as “views”. The features extracted from views can later be combined (i.e. stacking) t...

Invariant features play a key role in object and pattern recognition studies. Features that are invariant to geometrical transformations offer succinct representations of underlying objects so that they can be reliably identified. In this dissertation, we introduce a family of novel invariant features based on Cartan’s theory of moving frames. We call these new features summation invariants. Co...

This paper shows how we can make advantage of using genetic programming in selection of suitable features for automatic modulation recognition. Automatic modulation recognition is one of the essential components of modern receivers. In this regard, selection of suitable features may significantly affect the performance of the process. Simulations were conducted with 5db and 10db SNRs. Test and ...