In traditional text-based image annotations, the images are manually annotated by humans, and the annotations are used as an index for image retrieval [13, 14].
We thank P. Fischer for manual image annotations.
The proposed architecture addresses the issues of keyword based image retrieval and content-based image retrieval through the use of qualitative spatial representations over semantic image annotations.
Furthermore, informatics databases that allow incorporation of image features and image annotations, along with medical and genetic data, have to be generated.
To address this problem, this paper proposes an unsupervised concept-based image indexing technique which uses a lexical ontology to extract semantic signatures called 'semantic chromosomes' from image annotations.
Thanks to image data from the Lab of Ornithology, and thousands of volunteers who worked on uploading bird taxonomy, the app has more than a million crowdsourced image annotations.
Although image annotations for most categories are valid and correct, interior images of vessels are also present in MARVEL dataset.
In [3], Russell et al. proposed LabelMe, a web-based open tool that allows polygon-based image annotations.
One day after note-taking app Evernote announced image annotations for its Windows version, today it's Android's turn for some attention.
The main difficulty of this approach is that many image annotations may be inherently noisy and incomplete.
