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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sopov, Evgeny Ivanov, Ilia |
| Copyright Year | 2014 |
| Description | Author affiliation: Institute of Computer Science and Telecommunications, Siberian State Aerospace University, Krasnoyarsk, Russia (Sopov, Evgeny; Ivanov, Ilia) |
| Abstract | The efficiency of HCI systems can be sufficiently improved by the analysis of additional contextual information about the human user and interaction process. The processing of visual context provides HCI with such information as user identification, age, gender, emotion recognition and others. In this work, an approach to adaptive model building for image classification is presented. The novelty search based upon the multi-objective genetic algorithm is used to stochastically design a variety of independent technologies, which provide different image analysis strategies. Finally, the ensemble based decision is built adaptively for the given image analysis problem. |
| Sponsorship | INSTICC |
| Starting Page | 832 |
| Ending Page | 839 |
| File Size | 361255 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9789897580628 |
| DOI | 10.5220/0005147108320839 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-01 |
| Publisher Place | Austria |
| Access Restriction | Subscribed |
| Rights Holder | SCITEPRESS |
| Subject Keyword | Algorithm design and analysis Image analysis Image recognition Sociology Novelty Search Classification Feature extraction Search problems Image Analysis Multiobjective Genetic Algorithm Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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