Abstract
Through the success of deep convolutional neural networks (CNN) for image classification and semantic concepts detection, the multimedia retrieval community provides interesting image analysing approaches and tools in order to deliver accurate semantic interpretation. Never the less, such approaches still focusing only on explicit information and objects that exist in content. Considering that implicit information could enhance the semantic interpretation, we are interested in a knowledge based framework to detect the semantic context. In this paper, we discuss a fuzzy ontology based approach for understanding image content through the detection of the contained context. We conducted preliminary experiments on the ImageNET2017 dataset. While the obtained results still not impressive, many open research direction could be tackled. Indeed, we think that a deep based knowledge management (in particular knowledge extraction and reasoning) could be considered as interesting and promising.