As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). To this end, a novel Folded-PCA is proposed, in which the spectral vector is folded into a matrix to allow the covariance matrix to ...

The most common type of cancer seen in women is breast cancer. To enable recovery from this severe disease, monitoring and early detection must be provided, and related precautions must be taken as a first step. During diagnosis, some cases may be overlooked due to fatigue and eyestrain, because the determination of abnormalities is a repetitive procedure. In this study, a computer-aided diagno...

This paper proposes a novel system for monitoring the health of underground pipelines. Some of these pipelines transport dangerous contents and any damage incurred might have catastrophic consequences. However, most of these damage are unintentional and usually a result of surrounding construction activities. In order to prevent these potential damages, monitoring systems are indispensable. Thi...

In this paper two methods for human face recognition and the influence of location mistakes are shown. First one, Principal Components Analysis (PCA), has been one of the most applied methods to perform face verification in 2D. In our experiments three classifiers have been considered to test influence of location errors in face verification using PCA. An initial set of “correct located faces” ...

Hyperspectral images (HSI) provide rich information which may not be captured by other sensing technologies and therefore gradually find a wide range of applications. However, they also generate a large amount of irrelevant or redundant data for a specific task. This causes a number of issues including significantly increased computation time, complexity and scale of prediction models mapping t...

سلج 36 روم 07 / 02 / 94 و يس و دصكي نيمشش يشهوژپ ياروش هسلج تروص 1 . هسلج ليكشت تعاس و خيرات ،زور : زور هبنشود خيرات هب 07 / 02 / 94 هسلج نامز تدم 2 زا تعاس 14 تياغل 16 2 . يدعب هسلج خيرات : 28 / 02 / 94 3 . هسلج ليكشت لحم : يشهوژپ تنواعم رتفد 4 . هسلج رد هدننك تكرش ءاضعا : 1 ناراجشا يلع رتكد 2 رتكد يمولظم يلع رف 3 رفدنمجرا سابع رتكد 4 يرفعج دمحم رتكد يدنره 5 يضاق ديعس رتكد يبرغم ...

To realize the classification of lubricating oil types using mid-infrared (MIR) spectroscopy, linear discriminant analysis (LDA) was used for dimensionality reduction spectrum data, and model established based on support vector machine (SVM). The spectra samples were pre-processed by interval selection, Savitzky–Golay smoothing, multiple scattering correction, normalization. Kennard–Stone algor...

* لوئسم هدنسيون : فيرـش نابايخ ،ناهفصا يوـك ،يـفقاو نب ،يناطلس نسحم ديهش حرف تسب كلاپ ،شخب 10 / 8 نفلت : 3168058 0913 email: [email protected] فده و هنيمز : ميزنآ نيرتمهم زا زانژيسكا ولكيس ميزنآ نيدنلاگاتسورپ زتنس ريسم ياه ا شياديپ و اه ندب رد باهتل تسا ناسنا . هزات رد رثا تاقيقحت نيرت ت رخ ي زانژيسكا ولكيس ميزنا زا يب 2 لولس رب هدش هديد ناسنا زغم يبصع ياه ب تسا ه يروط...

Handwritten digit recognition has always been a challenging task in pattern recognition area. In this paper we explore the performance of support vector machines (SVM) and principal component analysis (PCA) on handwritten digits recognition. The performance of SVM on handwritten digits recognition task is compared with three typical classification methods, i.e., linear discriminant classifiers ...

Abbreviations ChIP Chromatin immunoprecipitation EST Expressed sequence tag ORF Open reading frame PCA Principle component analysis SAGE Serial analysis of gene expression SOM Self-organizing map SVM Support vector machine