نتایج جستجو برای: feature extraction
تعداد نتایج: 373831 فیلتر نتایج به سال:
feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of local binary pattern features. in this paper, we investigate the use of local binary patterns for percep...
Feature extraction is a very important preprocessing step for classification of hyperspectral images. The linear discriminant analysis (LDA) method fails to work in small sample size situations. Moreover, LDA has poor efficiency for non-Gaussian data. LDA is optimized by a global criterion. Thus, it is not sufficiently flexible to cope with the multi-modal distributed data. We propose a new fea...
methods in this research, we utilized the chaos theory and fractal analysis in the interpretation of breast tumors on dce-mri. this cross-sectional study was done at pardisnoor imaging center during years 2015 and 2016 in iran. our sample size was 18 mass lesions, which were randomly selected among patients with birad 3 and birad 4 classification by the expert radiologist. the analysis was perf...
Feature extraction performs an important role in improving hyperspectral image classification. Compared with parametric methods, nonparametric feature extraction methods have better performance when classes have no normal distribution. Besides, these methods can extract more features than what parametric feature extraction methods do. Nonparametric feature extraction methods use nonparametric s...
Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for percep...
In pattern recognition, features are denoting some measurable characteristics of an observed phenomenon and feature extraction is the procedure of measuring these characteristics. A set of features can be expressed by a feature vector which is used as the input data of a system. An efficient feature extraction method can improve the performance of a machine learning system such as face recognit...
in this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fmri) data. in the preprocessing step, the number of fmri time points is reduced using principal component analysis (pca). then, independent component analysis (ica) is used for further data analysis. it estimates independent components (ics) of...
opinion mining deals with an analysis of user reviews for extracting their opinions, sentiments and demands in a specific area, which can play an important role in making major decisions in such area. in general, opinion mining extracts user reviews at three levels of document, sentence and feature. opinion mining at the feature level is taken into consideration more than the other two levels d...
One of the most preprocessing steps before the classification of hyperspectral images is supervised feature extraction. Because obtaining the training samples is hard and time consuming, the number of available training samples is limited. We propose a supervised feature extraction method in this paper that is efficient in small sample size situation. The proposed method, which is called weight...
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