Pedestrian Classification Based on Full-SVM Decision Tree

Pedestrian Classification Based on Full-SVM Decision Tree

Visual analysis has potential to be used for recognition, and it is one of the hottest but most difficult subjects in computer vision. In order to identify pedestrian movement in an Intelligent Security Monitoring System, the video activity in the prospect is represented by a series of spatio-temporal interest points. Since human posture has the characteristics of uncertainty and illegibility, ...

Multiclass Text Classification A Decision Tree based SVM Approach

This paper discusses about combining Support Vector Machine and decision trees for multi class text classification. Support Vector Machines are trained on each class at each level of the tree and the SVM which is more successful in predicting a class at that level is selected as the decision in that node. Thus a tree is constructed with different SVM in each node. And the tree constructed is us...

SVM Aggregating Intelligence: SVM, SVM Ensemble, SVM Classification Tree, and Evolving SVM Classification Tree

This article scopes a concept of SVM aggregating intelligence as 3 levels research: aggregating for a better machine learning performance, aggregating for an adaptive/dynamic intelligent system, and aggregating for multitask and life-long continuous machine learning, and reviews existing SVM aggregating methods including SVM ensemble, SVM classification tree, and evolving SVM classification tree.

SVM Aggregation : SVM , SVM Ensemble , SVM Classification Tree

Classification of polarimetric radar images based on SVM and BGSA

Classification of land cover is one of the most important applications of radar polarimetry images. The purpose of image classification is to classify image pixels into different classes based on vector properties of the extractor. Radar imaging systems provide useful information about ground cover by using a wide range of electromagnetic waves to image the Earthchr('39')s surface. The purpose ...