Supplementary Material: Diverse Image Annotation

Fuzzy Neighbor Voting for Automatic Image Annotation

With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper,...

Tags Re-ranking Using Multi-level Features in Automatic Image Annotation

Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative effect on the query's result. In this paper, a new method is presented for automatic image...

Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models

Supplementary Material for Fast Zero-Shot Image Tagging

We present another set of experiments conducted on the widely used IAPRTC-12 [6] dataset. We use the same tag annotation and image training-test split as described in [7] for our experiments. There are 291 unique tags and 19627 images in IAPRTC12. The dataset is split to 17341 training images and 2286 testing images. We further separate 15% from the training images as our validation set. Table ...

Filling annotation gaps in yeast genomes using genome-wide contact maps

MOTIVATIONS De novo sequencing of genomes is followed by annotation analyses aiming at identifying functional genomic features such as genes, non-coding RNAs or regulatory sequences, taking advantage of diverse datasets. These steps sometimes fail at detecting non-coding functional sequences: for example, origins of replication, centromeres and rDNA positions have proven difficult to annotate w...