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» Evaluation and benchmark for biological image segmentation
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IJON
2008
186views more  IJON 2008»
14 years 9 months ago
Computational analysis and learning for a biologically motivated model of boundary detection
In this work we address the problem of boundary detection by combining ideas and approaches from biological and computational vision. Initially, we propose a simple and efficient ...
Iasonas Kokkinos, Rachid Deriche, Olivier D. Fauge...
ICIP
2009
IEEE
15 years 10 months ago
Illumination Invariant Unsupervised Segmenter
A novel illumination invariant unsupervised multispectral texture segmentation method with unknown number of classes is presented. Multispectral texture mosaics are locally repres...
95
Voted
CVPR
2012
IEEE
13 years 3 days ago
Learning to segment dense cell nuclei with shape prior
We study the problem of segmenting multiple cell nuclei from GFP or Hoechst stained microscope images with a shape prior. This problem is encountered ubiquitously in cell biology ...
Xinghua Lou, Ullrich Köthe, Jochen Wittbrodt,...
CVPR
2006
IEEE
15 years 11 months ago
Image-Segmentation Evaluation From the Perspective of Salient Object Extraction
Image segmentation and its performance evaluation are very difficult but important problems in computer vision. A major challenge in segmentation evaluation comes from the fundame...
Feng Ge, Song Wang, Tiecheng Liu
PR
2010
163views more  PR 2010»
14 years 8 months ago
A comparative evaluation of interactive segmentation algorithms
In this paper we present a comparative evaluation of four popular interactive segmentation algorithms. The evaluation was carried out as a series of user-experiments, in which par...
Kevin McGuinness, Noel E. O'Connor