Semantic analysis of multimedia content is an on going research

area that has gained a lot of attention over the last few years.

Additionally, machine learning techniques are widely used for multimedia

analysis with great success. This work presents a combined approach

to semantic adaptation of neural network classifiers in multimedia fr a mework.

It is based on a fuzzy reasoning engine which is able to evaluate

the outputs and the confidence levels of the neural network classifier, using

a knowledge base. Improved image segmentation results are obtained,

which are used for adaptation of the network classifier, further increasing

its ability to provide accurate classification of the specific content.相关搜索： neural
fuzzy
content
base
Neural
Network
Classifier
fuzzy
neural
network