Hybrid Generative/Discriminative Learning for Automatic Image Annotation

Automatic Image Annotation (AIA) raises tremendous challenges to machine learning as it requires modeling of data that are both ambiguous in input and output, e.g., images containing multiple objects and labeled with multiple semantic tags. Even more challenging is that the number of candidate tags is usually huge (As large as the vocabulary size) yet each image is only related to a few of them. This paper presents a hybrid generative-discriminative classifier to simultaneously address the extreme data-ambiguity and overfitting-vulnerability issues in tasks such as AIA.

Provided by: Georgia Institute of Technology Topic: Big Data Date Added: Aug 2010 Format: PDF

Download Now

Find By Topic