ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
This work presents a novel approach in automatic detection of the lung nodules and is compared with respect to parametric nodule models in terms of sensitivity and specificity. A ...
102
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
In this paper, we propose a novel image similarity learning approach based on Probabilistic Feature Matching (PFM). We consider the matching process as the bipartite graph matchin...
123
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
In this paper we propose a cascaded hierarchical framework for object detection and tracking. We claim that, by integrating both detection and tracking into a unified framework, t...
61
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
The joint usage of low
104
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
One of the most severe problems in hybrid video coding is its block-based approach, which leads to distortions called blocking artifacts. These artifacts affect not only the subje...
67
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
143
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
Temporal prediction in standard video coding is performed in the spatial domain, where each pixel is predicted from a motioncompensated reconstructed pixel in a prior frame. This ...
111
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
We present in this paper a supervised approach for automatic detection of micro-calcifications. The system is based on learning the different morphology of the micro-calcification...
96
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
In this paper, we propose an approach for fast pedestrian detection in images. Inspired by the histogram of oriented gradient (HOG) features, a set of multi-scale orientation (MSO...
102
Voted
ICIP
2010
IEEE
14 years 10 months ago
2010
IEEE
Discovering local geometry of low-dimensional manifold embedded into a high-dimensional space has been widely studied in the literature of machine learning. Counter-intuitively, w...