TY - GEN
T1 - Image classification using marginalized kernels for graphs
AU - Aldea, Emanuel
AU - Atif, Jamal
AU - Bloch, Isabelle
PY - 2007/1/1
Y1 - 2007/1/1
N2 - We propose in this article an image classification technique based on kernel methods and graphs. Our work explores the possibility of applying marginalized kernels to image processing. In machine learning, performant algorithms have been developed for data organized as real valued arrays; these algorithms are used for various purposes like classification or regression. However, they are inappropriate for direct use on complex data sets. Our work consists of two distinct parts. In the first one we model the images by graphs to be able to represent their structural properties and inherent attributes. In the second one, we use kernel functions to project the graphs in a mathematical space that allows the use of performant classification algorithms. Experiments are performed on medical images acquired with various modalities and concerning different parts of the body.
AB - We propose in this article an image classification technique based on kernel methods and graphs. Our work explores the possibility of applying marginalized kernels to image processing. In machine learning, performant algorithms have been developed for data organized as real valued arrays; these algorithms are used for various purposes like classification or regression. However, they are inappropriate for direct use on complex data sets. Our work consists of two distinct parts. In the first one we model the images by graphs to be able to represent their structural properties and inherent attributes. In the second one, we use kernel functions to project the graphs in a mathematical space that allows the use of performant classification algorithms. Experiments are performed on medical images acquired with various modalities and concerning different parts of the body.
UR - https://www.scopus.com/pages/publications/38149108305
U2 - 10.1007/978-3-540-72903-7_10
DO - 10.1007/978-3-540-72903-7_10
M3 - Conference contribution
AN - SCOPUS:38149108305
SN - 9783540729020
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 103
EP - 113
BT - Graph-Based Representations in Pattern Recognition - 6th IAPR-TC-15 International Workshop, GbRPR 2007, Proceedings
PB - Springer Verlag
T2 - 6th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2007
Y2 - 11 June 2007 through 13 June 2007
ER -