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Marr–Hildreth algorithm

Known as: Marr (disambiguation), Marr-Hildreth, Marr-Hildreth algorithm 
In computer vision, the Marr–Hildreth algorithm is a method of detecting edges in digital images, that is, continuous curves where there are strong… Expand
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Highly Cited
2011
Highly Cited
2011
Interpretation of image contents is one of the objectives in computer vision specifically in image processing. In this era it has… Expand
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Highly Cited
2005
Highly Cited
2005
ing the sustainable use of rangelands for livestock production. However, many ecosystem components and Growing interest in the… Expand
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2004
2004
  • Chuan-Yu Chang
  • IEEE International Conference on Multimedia and…
  • 2004
  • Corpus ID: 12817139
In this paper, the special design of a Hopfield neural network, called contextual Hopfield neural network (CHNN), is presented… Expand
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Highly Cited
2003
Highly Cited
2003
Rangelands are grasslands, shrublands, and savannas used by wildlife for habitat and livestock in order to produce food and fiber… Expand
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2003
2003
Outlining of boundaries of organs and tumors in CT and MRI images are prerequisite in medical applications. In this paper, a… Expand
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Highly Cited
2002
Highly Cited
2002
Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of… Expand
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1994
1994
  • S. Sandor, R. Leahy
  • Proceedings of 1st International Conference on…
  • 1994
  • Corpus ID: 1484834
We describe a method for automatically labelling regions of three-dimensional (3-D) Magnetic Resonance (MR) scans of human brains… Expand
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Highly Cited
1993
Highly Cited
1993
Abstract A method of contrast enhancement for digital images is provided. As the method uses the LoG (Laplacian-of-a-Gaussian… Expand
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1990
1990
This study was an effort to establish the construct validity of measures designed to assess topical knowledge. We began with the… Expand
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1987
1987
In diesem Artikel wird die dreidimensionale Erweiterung des Marr-Hildreth Operators zur Segmentation von Volumendaten der… Expand
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