Semantic Information Extraction using Deep Learning
Lead Research Organisation:
University of Surrey
Department Name: Vision Speech and Signal Proc CVSSP
Abstract
Semantic Information Retrieval The research will focus on extraction of meaningful and actionable information from big
data by developing novel algorithms in areas of machine learning and information theory. There will be two main focuses
(1) extract semantic attribute and relationship between attributes as well as semantic captions for given multimedia input,
(2) given semantic attributes or caption, retrieve relevant multimedia files from databases. A typical AI algorithm classifies
inputs into different predefined classes and suppresses visual information which is irrelevant to predefined classes.
Extraction of semantic captions will allow AI algorithms to build a much richer representation of the underlying visual data.
data by developing novel algorithms in areas of machine learning and information theory. There will be two main focuses
(1) extract semantic attribute and relationship between attributes as well as semantic captions for given multimedia input,
(2) given semantic attributes or caption, retrieve relevant multimedia files from databases. A typical AI algorithm classifies
inputs into different predefined classes and suppresses visual information which is irrelevant to predefined classes.
Extraction of semantic captions will allow AI algorithms to build a much richer representation of the underlying visual data.
Organisations
People |
ORCID iD |
| Klaus Moessner (Primary Supervisor) | |
| Ammarah Farooq (Student) |