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99
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CVIU
2004
115views more  CVIU 2004»
15 years 13 days ago
Dynamic learning from multiple examples for semantic object segmentation and search
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...
Yaowu Xu, Eli Saber, A. Murat Tekalp
139
Voted

Source Code
7589views
16 years 8 months ago
MATLAB and Octave Functions for Computer Vision and Image Processing
Great Matlab and Octave function implementation for hot computer vision algorithms such as Feature detection via Phase Congruency, Spatial feature detection, Non-maxima suppression...
P. D. Kovesi
ICDAR
2005
IEEE
15 years 6 months ago
Text/Graphic labelling of Ancient Printed Documents
This paper presents a text/graphic labelling for ancient printed documents. Our approach is based on the extraction and the quantification of the various orientations that are pre...
Nicholas Journet, Véronique Eglin, Jean-Yve...
85
Voted
ISBI
2007
IEEE
15 years 6 months ago
Noise and Artifact Removal in Knife-Edge Scanning Microscopy
Knife-Edge Scanning Microscopy (KESM) is a recently developed technique that allows fast and automated imaging of several hundred cubic millimeters of tissue at sub-micron resolut...
David Mayerich, Bruce H. McCormick, John Keyser
MICCAI
1998
Springer
15 years 4 months ago
Constrained Elastic Surface Nets: Generating Smooth Surfaces from Binary Segmented Data
This paper describes a method for creating object surfaces from binary-segmented data that are free from aliasing and terracing artifacts. In this method, a net of linked surface n...
Sarah F. Frisken Gibson