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In order to identify a large number of very similar objects, a novel recognition approach is proposed by mean of combination of two dynamic grouping algorithms, the visual processing mechanism, PCA and multi-pathway SVM. The samples have been segmented to appropriate groups by grouping features, and then features with rotation invariance and translation invariance of each group are extracted. Finally,...
This paper proposes a method to identify and assess different levels of anger from the speech utterances. Unlike the existing methods which only detect the emotion from speech, the proposed method not only detects but also labels the level of an emotion. A 75 dimensional feature vector has been extracted from each audio clip and is used for training and testing. For classification and assessment the...
This paper aims that analysing neural network method in pattern recognition. A neural network is a processing device, whose design was inspired by the design and functioning of human brain and their components. The proposed solutions focus on applying Adaptive Resonance Theory model for pattern recognition. The primary function of which is to retrieve in a pattern stored in memory, when an incomplete...
A novel approach was developed to recognize vowels from continuous tongue and lip movements. Vowels were classified based on movement patterns (rather than on derived articulatory features, e.g., lip opening) using a machine learning approach. Recognition accuracy on a single-speaker dataset was 94.02% with a very short latency. Recognition accuracy was better for high vowels than for low vowels....
In this paper we address the issue of recognizing nonstandard Malaysian car license plates. These plates contain nonstandard characters such as italic, cursive and connected letters, which most plate recognition systems are unable to recognize. We propose a technique using stroke extraction and analysis to recognize these nonstandard characters. The proposed technique first extracts the contour of...
Evolutionary algorithms for selecting support vector machine (SVM) parameter values which are based on genetic algorithm and particle swarm optimization algorithm are researched in this paper, these algorithms have been successfully applied to the real underwater echo target recognition. Experimental comparison and analysis show that the evolutionary algorithms can identify optimal or near optimal...
Human posture recognition is gaining increasing attention in the fields of artificial intelligence and computer vision due to its promising applications in the areas of personal health care, environmental awareness, human-computer-interaction and surveillance systems. Human posture recognition in video sequences is a challenging task which is part of the more comprehensive problem of video sequence...
Defect detection and classification is crucial in ensuring product quality and reliability. Classification provides information on problems related to the detected defects which can then be used to perform yield prediction, fault diagnosis, correcting manufacturing issues and process control. Accurate classification requires good selection of features to help distinguish between different cluster...
In this paper, a new constructive training algorithm for feed forward MLP neural networks has been developed for isolated word recognition. An incremental training procedure has been employed where the training patterns are learned incrementally, i.e one by one. This algorithm started with a single training pattern and a single hidden-layer using one neuron. During neural network training, the hidden...
The feature subset selection is a key preprocessing part in the detection of the stored-grain insects based on the image recognition technology. According to the global optimization ability of the particle swarm optimization (PSO) and the superior classification performance of the support vector machines (SVM), this study proposed a method based on PSO and SVM to improve the classification accuracy...
A novel working angle recognition system of screw compressor valve using wavelets and Probabilistic Neural Networks for engineering application is proposed. According to tested valve vibration signal energy changing characteristic under different working angle of valve flake, the paper obtains vibration signal power distribution on different scales using continuous wavelet transform, that is, scale-wavelet...
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