Type

Conference Proceedings

Authors

Noel E. O'Connor
Remi Trichet

Subjects

Mathematics

Topics
svm extreme value theory computer vision image processing machine learning flexible object detection tasks

A flexible ensemble-SVM for computer vision tasks (2016)

Abstract This paper presents an ensemble-SVM method that features a data selection mechanism with stochastic and deterministic properties, the use of extreme value theory for classifier calibration, and the introduction of random forest for classifier combination. We applied the proposed algorithm to 2 event recognition datasets and the PASCAL2007 object detection dataset and compared it to single SVM and common computer vision ensemble-SVM methods. Our algorithm outperforms its competitors and shows a considerable boost on datasets with a limited amount of outliers.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science: Image processing
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Electronic Engineering
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics
Ireland -> Dublin City University -> Subject = Computer Science: Machine learning

Full list of authors on original publication

Noel E. O'Connor, Remi Trichet

Experts in our system

1
Noel E. O'Connor
Dublin City University
Total Publications: 420
 
2
Remi Trichet
Dublin City University
Total Publications: 4