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Visual Object Recognition with Supervised Learning
May/June 2003 (vol. 18 no. 3)
pp. 38-42
ASCII Text
x 
 
Bernd Heisele, "Visual Object Recognition with Supervised Learning," IEEE Intelligent Systems, vol. 18, no. 3, pp. 38-42, May/June, 2003.
 
 
BibTex
x
 
@article{ 10.1109/MIS.2003.1200726,
author = {Bernd Heisele},
title = {Visual Object Recognition with Supervised Learning},
journal ={IEEE Intelligent Systems},
volume = {18},
number = {3},
issn = {1541-1672},
year = {2003},
pages = {38-42},
doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2003.1200726},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Intelligent Systems
TI - Visual Object Recognition with Supervised Learning
IS - 3
SN - 1541-1672
SP38
EP42
EPD - 38-42
A1 - Bernd Heisele,
PY - 2003
KW - object detection
KW - object categorization
KW - object recognition
KW - visual learning
KW - pattern classification
KW - support vector machines
VL - 18
JA - IEEE Intelligent Systems
ER -
 
Bernd Heisele, MIT Center for Biological and Computational Learning

The problem of learning is arguably at the core of the problem of intelligence, both biological and artificial. This article reviews an approach to the problem of visual object recognition based on supervised learning. After briefly presenting the theoretical background, the author focuses on computer vision applications and discusses the problems and directions of future research.

Index Terms:
object detection, object categorization, object recognition, visual learning, pattern classification, support vector machines
Citation:
Bernd Heisele, "Visual Object Recognition with Supervised Learning," IEEE Intelligent Systems, vol. 18, no. 3, pp. 38-42, May/June 2003, doi:10.1109/MIS.2003.1200726
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