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» Learning Contextual Metrics for Automatic Image Annotation
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CVPR
2010
IEEE
14 years 3 months ago
Building and Using a Semantivisual Image Hierarchy
A semantically meaningful image hierarchy can ease the human effort in organizing thousands and millions of pictures (e.g., personal albums), and help to improve performance of en...
Li-Jia Li, Chong Wang, Yongwhan Lim, David Blei, L...
ICCV
2007
IEEE
14 years 1 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...
DAGM
2008
Springer
13 years 9 months ago
A Multiple Kernel Learning Approach to Joint Multi-class Object Detection
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
Christoph H. Lampert, Matthew B. Blaschko
CVPR
2012
IEEE
11 years 10 months ago
Large-scale knowledge transfer for object localization in ImageNet
ImageNet is a large-scale database of object classes with millions of images. Unfortunately only a small fraction of them is manually annotated with bounding-boxes. This prevents ...
Matthieu Guillaumin, Vittorio Ferrari
ICIP
2002
IEEE
14 years 9 months ago
Semantic based categorization, browsing and retrieval in medical image databases
Content-based retrieval (CBIR) methods in medical databases have been designed to support specific tasks, such as retrieval of digital mammograms or 3D MRI images. These methods c...
Aleksandra Mojsilovic, José Gomes