نتایج جستجو برای: svm classifier

تعداد نتایج: 59967  

Journal: :The Journal of the Korean Institute of Information and Communication Engineering 2010

Journal: :International Journal of Advanced Trends in Computer Science and Engineering 2020

Journal: :NeuroImage 2013
Rik Vandenberghe Natalie Nelissen Eric Salmon Adrian Ivanoiu Steen G. Hasselbalch Allan Andersen Alex Korner Lennart Minthon David J. Brooks Koen Van Laere Patrick Dupont

(18)F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as 'normal' versus 'Alzheimer-like', is of high clinical relevance. We evaluated whether a supervised machine learning technique, support vector machines (SVM), can replicate the assignments made by visual readers blind to the clinical diagnosis...

Journal: :Wireless Personal Communications 2017
Yantao Li Gang Zhou Bin Nie

Web caching is a significantly important strategy for improving Web performance. In this paper, we design SmartCache, a router-based system of Web page load time reduction in home broadband access networks, which is composed of cache, SVM trainer and classifier, and browser extension. More specifically, the browser interacts with users to collect their experience satisfaction and prepare traini...

Journal: :JCM 2015
Jie Cao Zhiyi Fang Dan Zhang Guannan Qu

Abstract—Network traffic classification is the foundation of many network research works. In recent years, the research on traffic classification and identification based on machine learning method is a new research direction. Support Vector Machine (SVM) is the one of the machine learning method which performs good accuracy and stability. However, the traditional classification performance of...

Journal: :Journal of Korean Institute of Intelligent Systems 2005

Journal: :Medical ultrasonography 2013
Dan Mihai Mihăilescu Vasile Gui Corneliu Ioan Toma Alina Popescu Ioan Sporea

UNLABELLED In this paper we discuss the problem of computer aided evaluation of the severity of steatosis disease using ultrasound images. The AIM of the study being to compare the automatic evaluation of liver steatosis using random forests (RF) and support vector machine (SVM) classifiers. MATERIAL AND METHOD One hundred and twenty consecutive patients with steatosis or normal liver, assess...

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