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A Comparative analysis of spectral band selection techniques
... This Thesis is brought to you for free and open access by the Thesis/Dissertation Collections at RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For ... See full document
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A comparative analysis of biomarker selection techniques
... Feature selection has become the essential step in biomarker discovery from high-dimensional genomics ...feature selection techniques may result in diferent set of biomarkers, that is, diferent ... See full document
10
A comparative analysis on feature selection techniques for classification problems
... Feature selection has become the vital step in many data mining application for instances ...Feature selection eliminates irrelevant attribute to obtain high quality features that may contribute in ... See full document
12
Spectral fatigue analysis techniques
... narrow band solution, which introduces a rigorous assumption on the frequency distribution of the response ...narrow band solutions to a wide frequency band and introduce rainflow cycle counting in ... See full document
221
Band selection in spectral imaging for non-invasive melanoma diagnosis
... 3. Selection of spectral bands The number of samples in medical diagnosis is usually small and fortunately the number of melanoma lesions is usually much lower than the number of benign ...a band ... See full document
6
Semi-supervised hyperspectral band selection via spectral-spatial hypergraph model
... semi-supervised band selection. Sec- ondly, we introduce spectral and spatial information into hyperedge ...joint spectral spatial analysis has demonstrated significant advantages over ... See full document
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A novel approach to hyperspectral band selection based on spectral shape similarity analysis and fast branch and bound search
... the spectral resolution of the hyperspectral image data becomes denser, which results in large number of bands, high correlation between neighboring bands, and high data ...further analysis, such as land ... See full document
10
Comparative Study of Band-Power Extraction Techniques for Motor Imagery Classification
... We also compared the influence of performing a pre-filtering on the data. Some methods indeed benefit from such pre- filtering. As explained in section II-D, detrending the data by removing low-frequency components ... See full document
6
On the Utility of Power Spectral Techniques With Feature Selection Techniques for Effective Mental Task Classification in Noninvasive BCI
... feature selection is used to increase the ratio for the mental task classification by getting rid of irrelevant and superfluous ...power spectral density (PSD) using feature ...a comparative ... See full document
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Exploitation of Intra-Spectral Band Correlation for Rapid Feacture Selection and Target Identification in Hyperspectral Imagery
... Components Analysis for dimensionality reduction with a clustering algorithm which seeks to associate spectral rather than spatial ...similar spectral dimensions, the assumption of no a priori ... See full document
191
Comparative Analysis of Outlier Detection Techniques
... many techniques like ...feature selection techniques that are used essentially to remove the noise from the data distribution and focus on the main cluster of the normal data points while isolating ... See full document
10
Comparative Analysis of Image Denoising Techniques
... Impulse noise is caused by faulty camera sensors, faults in data acquisition systems and transmission in a noisy channel [5]. There are various methods that helps to remove noise from the image. But better performance ... See full document
5
Threshold selection in gene co-expression networks using spectral graph theory techniques
... further analysis. We believe that the primary strength of the spectral graph theory- based method presented here is that it is a systematic method for threshold ...combinatorial analysis and contain ... See full document
12
Advanced Spectral and Spatial Techniques for Hyperspectral Image Analysis and Classification
... the analysis, based on the above scenarios three experiments are designed as described ...image analysis is to ap- ply the PCA technique to the original image followed by the ...after selection does ... See full document
172
Similarity-Based Unsupervised Band Selection for Hyperspectral Image Analysis
... Abstract—Band selection is a common approach to reduce the data dimensionality of hyperspectral ...unsupervised band selection, the objective is to select the most distinctive and in- ... See full document
5
Comparative Study on Embedded Feature Selection Techniques for Internet Traffic Classification
... TaimurBakhshi, et.al,…[2] analyzed Traffic classification utilizing flow measurement enables operators to perform essential network management. Flow accounting methods such as NetFlow are, however, considered in adequate ... See full document
10
COMPARATIVE ANALYSIS OF VARIOUS QRS TECHNIQUES IN ECG
... Typically frequency components of a QRS complex range from about 10 Hz to about 25 Hz. Almost all QRS detection algorithms use a filter stage prior to the actual detection in order to attenuate other signal components ... See full document
8
Comparative Analysis of Software Defect Prediction Techniques
... includes selection of features and reduction of unnecessary ...relevance analysis, threshold-based cluster, feature selection, random sampling to differentiate between non-faulty and faulty in- ... See full document
7
Comparative Analysis of Clustering Techniques for Movie Recommendation
... This technique handled the stray data points in a more efficient way. It was able to group it to the most similar cluster. The clustering used here was more fine-tuned with ‘thinner’ cluster with respect to the total ... See full document
Spectral-Spatial Classification Integrating Band Selection for Hyperspectral Imagery With Severe Noise Bands
... detailed spectral and rich spatial information of hyperspectral images can be fully exploited to improve the classification ...a spectral-spatial conditional random field classification algorithm ... See full document
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