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ICCV
2009
IEEE
15 years 1 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
PAMI
2008
270views more  PAMI 2008»
13 years 8 months ago
Randomized Clustering Forests for Image Classification
This paper introduces three new contributions to the problems of image classification and image search. First, we propose a new image patch quantization algorithm. Other competitiv...
Frank Moosmann, Eric Nowak, Frédéric...
ICMCS
2000
IEEE
136views Multimedia» more  ICMCS 2000»
14 years 1 months ago
Low-Level Motion Activity Features for Semantic Characterization of Video
Efficient methods of content characterization for the browsing, retrieval or filtering of vast amount of digital video content has become a necessity. Still, there is a gap betwee...
Kadir A. Peker, A. Aydin Alatan, Ali N. Akansu
ICCV
2009
IEEE
15 years 1 months ago
Unlabeled data improves word prediction
Labeling image collections is a tedious task, especially when multiple labels have to be chosen for each image. In this paper we introduce a new framework that extends state of ...
Nicolas Loeff, Ali Farhadi, Ian Endres and David A...
BMCBI
2005
161views more  BMCBI 2005»
13 years 8 months ago
Non-linear mapping for exploratory data analysis in functional genomics
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
Francisco Azuaje, Haiying Wang, Alban Chesneau