Publication
Evaluation of random forests on large-scale classification problems using a bag-of-visual-words representation
Conference Article
Conference
Catalan Conference on Artificial Intelligence (CCIA)
Edition
17th
Pages
273-276
Doc link
http://dx.doi.org/10.3233/978-1-61499-452-7-273
File
Abstract
Random Forest is a very efficient classification method that has shown success in tasks like image segmentation or object detection, but has not been applied yet in large-scale image classification scenarios using a Bag-of-Visual-Words representation. In this work we evaluate the performance of Random Forest on the ImageNet dataset, and compare it to standard approaches in the state-of-the-art.
Categories
computer vision, image classification.
Author keywords
large-scale image classification, classifier forest, random forests
Scientific reference
X. Solé, A. Ramisa and C. Torras. Evaluation of random forests on large-scale classification problems using a bag-of-visual-words representation, 17th Catalan Conference on Artificial Intelligence, 2014, Barcelona, in Artificial Intelligence Research and Development, Vol 269 of Frontiers in Artificial Intelligence and Applications, pp. 273-276, 2014, IOS Press.
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