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» Toward Objective Evaluation of Image Segmentation Algorithms
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158
Voted
ICCV
2007
IEEE
15 years 10 months ago
Fast Automatic Heart Chamber Segmentation from 3D CT Data Using Marginal Space Learning and Steerable Features
Multi-chamber heart segmentation is a prerequisite for global quantification of the cardiac function. The complexity of cardiac anatomy, poor contrast, noise or motion artifacts ...
Yefeng Zheng, Adrian Barbu, Bogdan Georgescu, Mich...
87
Voted
CVPR
2010
IEEE
16 years 3 days ago
What is an object?
We present a generic objectness measure, quantifying how likely it is for an image window to contain an object of any class. We explicitly train it to distinguish objects with a...
Pierre America, Robin Milner, Oscar Nierstrasz, Ma...
138
Voted
CVPR
2010
IEEE
16 years 7 days ago
The Role of Features, Algorithms and Data in Visual Recognition
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of trainin...
Devi Parikh and C. Lawrence Zitnick
123
Voted
ISBI
2006
IEEE
16 years 4 months ago
Exact correction of sharply varying off-resonance effects in spiral MRI
Magnetic Resonance Imaging with non-Cartesian acquisition schemes suffer from blurring artifacts induced by offresonance. Conventional algorithms for off-resonance correction are ...
Mahender K. Makhijani, Krishna S. Nayak
120
Voted
CVPR
2010
IEEE
16 years 5 days ago
Analyzing Spatially-varying Blur
Blur is caused by a pixel receiving light from multiple scene points, and in many cases, such as object motion, the induced blur varies spatially across the image plane. However, ...
Ayan Chakrabarti, Todd Zickler, William Freeman