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ICCV
2005
IEEE
14 years 10 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
MICCAI
2006
Springer
14 years 9 months ago
Atlas Guided Identification of Brain Structures by Combining 3D Segmentation and SVM Classification
Abstract. This study presents a novel automatic approach for the identification of anatomical brain structures in magnetic resonance images (MRI). The method combines a fast multis...
Ayelet Akselrod-Ballin, Meirav Galun, Moshe John G...
MLMI
2005
Springer
14 years 2 months ago
Improving the Performance of Acoustic Event Classification by Selecting and Combining Information Sources Using the Fuzzy Integr
Acoustic events produced in meeting-room-like environments may carry information useful for perceptually aware interfaces. In this paper, we focus on the problem of combining diffe...
Andrey Temko, Dusan Macho, Climent Nadeu
MCS
2000
Springer
14 years 9 days ago
Combining Fisher Linear Discriminants for Dissimilarity Representations
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...
Elzbieta Pekalska, Marina Skurichina, Robert P. W....
NIPS
2008
13 years 10 months ago
Cascaded Classification Models: Combining Models for Holistic Scene Understanding
One of the original goals of computer vision was to fully understand a natural scene. This requires solving several sub-problems simultaneously, including object detection, region...
Geremy Heitz, Stephen Gould, Ashutosh Saxena, Daph...