CVPR
2012
IEEE
11 years 7 months ago
2012
IEEE
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
We propose a novel semi-supervised classifier for handwritten digit recognition problems that is based on the assumption that any digit can be obtained as a slight transformation...
NIPS
1998
1998
Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
13 years 6 months ago
This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
CVPR
2010
IEEE
14 years 1 months ago
2010
IEEE
We present a method to segment a collection of unlabeled images while exploiting automatically discovered appearance patterns shared between them. Given an unlabeled pool of multi...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
Current methods for learning visual categories work well when a large amount of labeled data is available, but can run into severe difficulties when the number of labeled examples...
CVPR
2006
IEEE
14 years 7 months ago
2006
IEEE
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
CVPR
2004
IEEE
14 years 7 months ago
2004
IEEE
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...