Texture classification is one of the problems which has been paid much attention on by computer scientists since late 90s. If texture classification is done correctly and accurately, it can be used in many cases such as Pattern recognition, object tracking, and shape recognition. So far, there have been so many methods offered to solve this problem. Near all these methods have tried to extract ...

This paper presents a new neural network approach to real-time pattern recognition on a given set of binary (or bipolar) sample patterns. The perceptive neuron of a binary pattern is defined and constructed as a binary neuron with a neighborhood perceptive field. Letting its hidden units be the respective perceptive neurons of the patterns, a three-layer forward neural network is constructed to...

There has been much recent interest in application of the pool-adjacent-violators (PAV) algorithm for the purpose of calibrating the probabilistic outputs of automatic pattern recognition and machine learning algorithms. Special cost functions, known as proper scoring rules form natural objective functions to judge the goodness of such calibration. We show that for binary pattern classifiers, t...

The field of face recognition is increasingly investigated for access control, face based search, passport processing, security, surveillance, etc. applications. Performance of face recognition systems under constrained environment is quite satisfactory, but face recognition in unconstrained environment is yet a challenging problem due to key technical challenging issues. Varying illumination i...

This paper presents a new method for facial expression recognition using divided local binary pattern features. Motivated by Fourier’s parity decomposition, we decompose a LBP descriptor into two subdescriptors. This method reduces the amount of data of the feature extraction, reducing the data dimension effectively. Experimental results on JAFFE facial expression database show that the propose...

Automatic code generation is frequently used to create implementations of algorithms specifically tuned particular hardware and application parameters. The process involves the selection adequate transformations, tuning parameters, parallelization strategies. We propose an alternative time-intensive autotuning, scenario-specific performance models, or black-box machine learning select best-perf...

An input-series output-parallel (ISOP) system, in which multiple converter modules are connected in series at the input sides and parallel at the output side, is very suitable for high input-voltage, low output-voltage, and high output-current applications. Input-voltage sharing (IVS) and output-current sharing of the constituent modules among the ISOP system must be ensured. The existing IVS c...