We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
In this paper we present a new scheme for detection and tracking of specific objects in a knowledge-based framework. The scheme uses a supervised learning method: Support Vector M...
Lionel Carminati, Jenny Benois-Pineau, Christian J...
In this paper, an efficient approach by combining the novel wavelet-based feature template, the support vector machine (SVM) classifier, and the wavelet entropy filtering is prese...
This paper presents a supervised approach for relation extraction. We apply Support Vector Machines to detect and classify the relations in Automatic Content Extraction (ACE) corpu...