Drone-vs-Bird Detection Grand Challenge at ICASSP2023

Coluccia, A; Fascista, A; Sommer, L; Schumann, A; Dimou, A; Zarpalas, D; Sharma, N

Drone-vs-Bird Detection Grand Challenge at ICASSP2023

Coluccia, A Fascista, A Sommer, L Schumann, A Dimou, A Zarpalas, D Sharma, N

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, 00, pp. 1-2
Issue Date:: 2024-02-14

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Field	Value	Language
dc.contributor.author	Coluccia, A
dc.contributor.author	Fascista, A
dc.contributor.author	Sommer, L
dc.contributor.author	Schumann, A
dc.contributor.author	Dimou, A
dc.contributor.author	Zarpalas, D
dc.contributor.author	Sharma, N https://orcid.org/0000-0003-0841-1245
dc.date	2023-06-04
dc.date.accessioned	2024-04-15T01:21:34Z
dc.date.available	2024-04-15T01:21:34Z
dc.date.issued	2024-02-14
dc.identifier.citation	ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, 00, pp. 1-2
dc.identifier.isbn	978-1-7281-6328-4
dc.identifier.issn	1520-6149
dc.identifier.uri	http://hdl.handle.net/10453/177913
dc.description.abstract	This paper presents the 6th edition of the Drone vs Bird Detection Grand Challenge organized within the 48th IEEE International Conference on Acoustics Speech and Signal Processing ICASSP Taking video samples recorded by commercial RGB cameras as input the challenge stimulates the design of advanced approaches capable of detecting the presence of small drones flying in a given area under surveillance Successful methods should ensure high detection rates while limiting the number of false alarms erroneously triggered in presence of very similar false targets birds The paper summarizes the novel methods proposed by the four participating teams that succeeded in providing satisfactory detection performance on the 2023 challenge dataset
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
dc.relation.ispartof	ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing
dc.relation.isbasedon	10.1109/icassp49357.2023.10433921
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Drone-vs-Bird Detection Grand Challenge at ICASSP2023
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Rhodes Island, Greece
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2024-04-15T01:21:32Z
pubs.finish-date	2023-06-10
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2023-06-04
pubs.volume	00
dc.location	Piscataway, USA

Abstract:

This paper presents the 6th edition of the Drone vs Bird Detection Grand Challenge organized within the 48th IEEE International Conference on Acoustics Speech and Signal Processing ICASSP Taking video samples recorded by commercial RGB cameras as input the challenge stimulates the design of advanced approaches capable of detecting the presence of small drones flying in a given area under surveillance Successful methods should ensure high detection rates while limiting the number of false alarms erroneously triggered in presence of very similar false targets birds The paper summarizes the novel methods proposed by the four participating teams that succeeded in providing satisfactory detection performance on the 2023 challenge dataset

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http://hdl.handle.net/10453/177913