Adaptive Boosting with SVM Classifier for Moving Vehicle Classification
نویسندگان
چکیده
منابع مشابه
Automatic Incident Classification for Big Traffic Data by Adaptive Boosting SVM
Modern cities experience heavy traffic flows and congestions regularly across space and time. Monitoring traffic situations becomes an important challenge for the Traffic Control and Surveillance Systems (TCSS). In advanced TCSS, it is helpful to automatically detect and classify different traffic incidents such as severity of congestion, abnormal driving pattern, abrupt or illegal stop on road...
متن کاملCortical Surface Thickness as a Classifier: Boosting for Autism Classification
We study the problem of classifying an autistic group from controls using structural image data alone, a task that requires a clinical interview with a psychologist. Because of the highly convoluted brain surface topology, feature extraction poses the first obstacle. A clinically relevant measure called the cortical thickness has shown promise but yields a rather challenging learning problem--w...
متن کاملA Hybrid Classifier Based on Svm Method for Cancer Classification
In this paper, we proposed a new method of applying Support Vector Machines (SVMs) for cancer classification. We proposed a hybrid classifier that considers the degree of a membership function of each class with the help of Fuzzy Naive Bayes (FNB) and then organizes one-versus-rest (OVR) SVMs as the architecture classifying into the corresponding class. In this method, we used a novel system of...
متن کاملAdaptive Intrusion Detection based on Boosting and Naïve Bayesian Classifier
In this paper, we introduce a new learning algorithm for adaptive intrusion detection using boosting and naïve Bayesian classifier, which considers a series of classifiers and combines the votes of each individual classifier for classifying an unknown or known example. The proposed algorithm generates the probability set for each round using naïve Bayesian classifier and updates the weights of ...
متن کاملSVM based classifier for Blogs
In this project a classifier is developed that can classify a blog into different categories based on the topics that author frequently writes about. Treating each blog as a document and each topic category as a class, a SVM based multi-class classifier is developed. The impact of feature selection has been studied by using different methods to generate the feature vector from the documents.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Engineering
سال: 2013
ISSN: 1877-7058
DOI: 10.1016/j.proeng.2013.02.054