DISA at ImageCLEF 2014 Revised: Search-based Image Annotation with DeCAF Features
Petra Budikova, Jan Botorek, Michal Batko, Pavel Zezula

TL;DR
This paper describes an improved image annotation system using DeCAF features and a new similarity search component, analyzing how search parameters affect annotation quality in the ImageCLEF 2014 challenge.
Contribution
Introduction of a new similarity search component integrated with DeCAF features for enhanced image annotation performance.
Findings
The new similarity search component improved annotation accuracy.
Different similarity search parameters significantly influence annotation quality.
System achieved competitive results in the ImageCLEF 2014 task.
Abstract
This paper constitutes an extension to the report on DISA-MU team participation in the ImageCLEF 2014 Scalable Concept Image Annotation Task as published in [3]. Specifically, we introduce a new similarity search component that was implemented into the system, report on the results achieved by utilizing this component, and analyze the influence of different similarity search parameters on the annotation quality.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsImage Retrieval and Classification Techniques · Advanced Image and Video Retrieval Techniques · Genomics and Phylogenetic Studies
