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This paper investigated a computer-aided diagnosis for breast mass classification by mammography examination using complemtarity existing between features and classifiers. It is concerned with the design and development of an automatic mass classification of mammograms. The proposed method consists of three stages: segmentation, feature extraction and classification. In classification phase, kernel...
Fingerprints are the most widely used biometric feature for person identification & verification in the field of biometric identification. Fingerprint possesâ two main types of features that are used for automatic fingerprint identification & verification (i) Ridge & furrow structure that forms a special pattern in the central region of finger...
Since Gabor features are robust to changes in illumination and facial expression and have been successfully applied for face recognition. The locality preserving projection (LPP) is nonorthogonal and makes it difficult to reconstruct the data. The orthogonal locality preserving projection (OLPP) produces orthogonal basis functions and can have more locality preserving power than LPP. OLPP has more...
The representation of input data set is important for learning task. In data summarization, the representation of the multi-instances stored in non-target tables that have many-to-one relationship with record stored in target table influences the descriptive accuracy of the summarized data. If the summarized data is fed into a classifier as one of the input features, the predictive accuracy of the...
In order to reduce the original algorithm's dependence on the primary matrix and raise the classification accuracy, we combine the five order Newton method and the steepest descent method. We also introduce punishing factors into algorithm, and apply them to the core of the iterative process of the Fast ICA algorithm, an improved kernel independent component analysis algorithm (KICA) is proposed in...
Machine vision is applied to detect wood knots and cracks, to classify strong and stable woods. In order to obtain effective and efficient classification a well-defined pattern recognition and feature extraction algorithms are essential. In this paper we examine three different methods for feature extraction; Gray level co-occurrence matrix (GLCM), Local binary patterns (LBP), and statistical moments...
In this paper, a new statistical-based ECG algorithm, which applies the idea of matching Reduced Binary Pattern, is proposed to seek a timely and accurate human identity recognition. A comparison with previous researches, the proposed design requires neither waveform complex information nor de-noising pre-processing in advance. Our algorithm is tested on the public MIT-BIH arrhythmia and normal sinus...
Texture images can be characterized with key features extracted from images. In this paper, the scale invariant feature transform (hereinafter SIFT) algorithm is utilized to generate local features for texture image classification. The local features are selected as inputs for texture classification framework. For each texture category, a texton dictionary is built based on the local features. To...
In this paper, a new method to manage graduation photography is introduced. First, AdaBoost algorithm, which can achieve high detection accuracy, is adopted to detect faces in the graduation photography. After adjusting the position and adding the missed faces, the personal information of each photography is added into database. To get the current status of graduates, one can send emails to the member...
In this paper, we propose a new approach for feature selection using fuzzy-ARTMAP classification and conflict characterization in fault diagnosis process. This approach is realized in two stages. In the first one, we classify the unfaulty functioning data of system using the fuzzy-ARTMAP classification. In the second stage, a conflict is accounted between features of test data based on the hyper-cubes...
In this paper, a novel hierarchical algorithm with multi-feature fusion is proposed for facial expression recognition. In this area, many people have proposed many good results, but few of them made good use of the distribution characteristic of facial expression itself. In the analysis of the feature distribution, we find happiness and surprise are clearly separated from the other expressions. So...
Due to its invariance to monotonic grayscale transformation and simple computation, Local Binary Pattern (LBP) is broadly used as feature extractor in face recognition tasks in recent years [3]. In previous work, people have proposed methods of using Adaboost to select most representative features in samples. Zhang et al. proposed a method applying Adaboost algorithm to select those most distinctive...
Action is any meaningful movement of the human and it is used to convey information or to interact naturally without any mechanical devices. Human action recognition is motivated by some of the applications such as video retrieval, Human robot interaction, to interact with deaf and dumb people etc. In any Action Recognition System, some pre-processing steps are done for removing the noise caused because...
The change in morphology, diameter, branching pattern and/or tortuosity of retinal blood vessels is an important indicator of various clinical disorders of the eye and the body. This paper reports a supervised methodology for segmentation of the retinal vasculature from ocular fundus images. A 7-D feature vector is constructed by computing the outputs of morphological linear operators, line strengths...
In automotive industry the safety of cars behavior is monitoring using computers. The information acquired on the bus communication is often redundant and not relevant. Therefore in the case of faults detection and isolation based on machine learning model, we need to reduce the number of variables according with their relevance and allowing taking decision in real time. In this paper, we propose...
In this paper, we improve cascade-Adaboost classifier and propose a cascade-Adaboost-SVM classifier. It is combined with Adaboost and SVM and real-time pedestrian detection system with a single camera. We capture the pedestrian candidate areas with a window of fixed size, conduct feature extraction to candidate areas and mobile images with Haar-like rectangle feature calculation and then, complete...
The tertiary structure of a protein molecule is the main factor which can be used to determine its chemical properties as well as its function. The knowledge of the protein function is crucial in the development of new drugs, better crops and synthetic biochemicals. With the rapid development in technology, the number of determined protein structures increases every day, so retrieving structurally...
The paper deals with the vocal emotion recognition which is a very important task for several applications in the field of human-machine interaction. There is a plenty of algorithms proposed up to date for this purpose that exploit different types of features and classifiers. Our previous work showed that high-level features perform very well in terms of emotion classification from speech. However,...
In this paper, we propose a novel affective video classification method based on facial expression recognition by learning the spatio-temporal feature fusion of actors' and viewers' facial expressions. For spatial features, we integrate Haar-like features into compositional ones according to the features' correlation, and train a mid classifier during the period. Then this process is embedded into...
This paper focus on the ECG signal classification based on the BP Neuron Network. The AR coefficients and relative errors were used to represent the ECG segments in current research. The data in the paper obtained from MIT-BIH database. It included Normal Sinus Rhythm (NSR), premature ventricular contraction (PVC), Ventricular Tachycardia (VT), and Ventricular Fibrillation (VF). The back propagation...
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