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» Learning the Relative Importance of Features in Image Data
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AIA
2007
15 years 5 months ago
A framework for generating data to simulate changing environments
A fundamental assumption often made in supervised classification is that the problem is static, i.e. the description of the classes does not change with time. However many practi...
Anand M. Narasimhamurthy, Ludmila I. Kuncheva
150
Voted
IEEEVAST
2010
14 years 11 months ago
Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological opera
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...
ICIP
1994
IEEE
15 years 7 months ago
Active Region Models for Segmenting Medical Images
This paper describes a new region-growing method for segmenting medical images. The method uses a closed snake driven by a pressure force that is a function of the statistical cha...
Jim Ivins, John Porrill
ICML
1996
IEEE
16 years 4 months ago
Searching for Structure in Multiple Streams of Data
Finding structure in multiple streams of data is an important problem. Consider the streams of data owing from a robot's sensors, the monitors in an intensive care unit, or p...
Tim Oates, Paul R. Cohen
IJCV
2007
163views more  IJCV 2007»
15 years 4 months ago
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
In this paper, we present a novel image representation that renders it possible to access natural scenes by local semantic description. Our work is motivated by the continuing effo...
Julia Vogel, Bernt Schiele