Deep supervised hashing for fast retrieval of radio image cubes

Stephen Ndung’u Machetho, Trienko L. Grobler, Stefan J. Wijnholds, Dimka Karastoyanova, George Azzopardi

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
32 Downloads (Pure)

Abstract

The shear number of sources that will be detected by next-generation radio surveys will be astronomical, which will result in serendipitous discoveries. Data-dependent deep hashing algorithms have been shown to be efficient at image retrieval tasks in the fields of computer vision and multimedia. However, there are limited applications of these methodologies in the field of astronomy. In this work, we utilize deep hashing to rapidly search for similar images in a large database. The experiment uses a balanced dataset of 2708 samples consisting of four classes: Compact, FRI, FRII, and Bent. The performance of the method was evaluated using the mean average precision (mAP) metric where a precision of 88.5% was achieved. The experimental results demonstrate the capability to search and retrieve similar radio images efficiently and at scale. The retrieval is based on the Hamming distance between the binary hash of the query image and those of the reference images in the database.

Original languageEnglish
Title of host publicationProceedings of the 35th URSI General Assembly and Scientific Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9789463968096
DOIs
Publication statusPublished - 3-Oct-2023
Event35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023 - Sapporo, Japan
Duration: 19-Aug-202326-Aug-2023

Publication series

Name2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023

Conference

Conference35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
Country/TerritoryJapan
CitySapporo
Period19/08/202326/08/2023

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