2019 IEEE International Symposium on Multimedia (ISM) 2019
DOI: 10.1109/ism46123.2019.00038
|View full text |Cite
|
Sign up to set email alerts
|

Efficient Indexing of Multiple Metric Spaces with Spectra

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
3
0
1

Year Published

2020
2020
2022
2022

Publication Types

Select...
2
1
1

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(4 citation statements)
references
References 24 publications
0
3
0
1
Order By: Relevance
“…In [Pereira and Ribeiro 2021], the authors employed visual features extracted from mammograms for the semantic annotation and classification of images using ontologies. Low-level features have been widely employed to validate the indexing capabilities of Metric Access Methods [Zabot et al 2019b, Moriyama et al 2021. Also, in [Maheshwari et al 2021] the authors employed various features to identify COVID-19 in images.…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations
“…In [Pereira and Ribeiro 2021], the authors employed visual features extracted from mammograms for the semantic annotation and classification of images using ontologies. Low-level features have been widely employed to validate the indexing capabilities of Metric Access Methods [Zabot et al 2019b, Moriyama et al 2021. Also, in [Maheshwari et al 2021] the authors employed various features to identify COVID-19 in images.…”
Section: Introductionmentioning
confidence: 99%
“…Previous use of data. A small part of FeatSet has been employed in the previous studies [Zabot et al 2019a, Zabot et al 2019b]. In that works, the authors explored different visual features to validate a novel Multi-Metric Access Method, aiming at indexing complex objects based on images' visual characteristics and the correlation among the distance spaces.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…A recuperação de dados complexos é frequentemente realizada a partir de comparações baseadas em Relações de Similaridade -RS, e são amplamente exploradas em diferentes tipos de domínios e em diversos trabalhos de Consultas por Similaridade sobre dados complexos armazenados em SGBDRs (RODRIGUES et al, 2020;ZABOT et al, 2019;CAZZOLATO et al, 2019a;VASCONCELOS et al, 2018). Tradicionalmente, consultas por similaridade executam comparações entre pares de representações extraídas sobre um conjunto de dados complexos, sobre os quais são frequentemente aplicados extratores de características, resultando em vetores de características.…”
Section: Lista De Ilustraçõesunclassified