MM
2006
ACM
14 years 6 months ago
2006
ACM
Conventional image categorization techniques primarily rely on low-level visual cues. In this paper, we describe a multimodal fusion scheme which improves the image classification...
IJCNN
2007
IEEE
14 years 6 months ago
2007
IEEE
— In this paper, a method based on wavelet coefficients in low-pass bands is proposed for the image classification with adaptive processing of data structures to organize a large...
ICPR
2006
IEEE
15 years 1 months ago
2006
IEEE
This article presents a method aiming at quantifying the visual similarity between two images. This kind of problem is recurrent in many applications such as object recognition, i...
ICIP
2004
IEEE
15 years 1 months ago
2004
IEEE
Image classification is an important task in computer vision. However, how to assign suitable labels to images is a subjective matter, especially when some images can be categoriz...
CVPR
2007
IEEE
2007
IEEE
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data
15 years 2 months ago
A popular approach to problems in image classification is to represent the image as a bag of visual words and then employ a classifier to categorize the image. Unfortunately, a si...
ICCV
2009
IEEE
15 years 5 months ago
2009
IEEE
In this paper we present a combined approach for ob-
ject localization and classification. Our contribution is two-
fold. (a) A contextual combination of localization and clas-
...
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Homepage Publication
One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...
CVPR
2009
IEEE
15 years 7 months ago
2009
IEEE
Image classification and annotation are important problems
in computer vision, but rarely considered together. Intuitively,
annotations provide evidence for the class label,
and...
CVPR
2009
IEEE
15 years 7 months ago
2009
IEEE
Recently SVMs using spatial pyramid matching (SPM)
kernel have been highly successful in image classification.
Despite its popularity, these nonlinear SVMs have a complexity
O(n...