English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Recognition of emotional semantics in images is a new and very challenging research direction that gains more and more attention in the research community. As an emerging topic, publications remains relatively rare and numerous issues need to be addressed. In this paper, we propose to investigate the efficiency of different types of features including low-level features and proposed semantic features for classification of emotional semantics in images. Moreover, we propose a new approach that combines different classifiers based on Dempster-Shafer’s theory of evidence, which has the ability to handle ambiguous and uncertain knowledge such as the properties of emotions. Experiments driven on the International Affective Picture System (IAPS) image databases, which is a common stimulus set frequently used in emotion psychology research, demonstrated that the proposed approach can achieve promising results.

EVALUATION OF FEATURES AND COMBINATION APPROACHES FOR THE CLASSIFICATION OF EMOTIONAL SEMANTICS IN IMAGES