Graph-Based Early-Fusion for Flood Detection

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Standard

Graph-Based Early-Fusion for Flood Detection. / De Werneck, Rafael O.; Dourado, Icaro C.; Fadel, Samuel G. et al.
2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings. IEEE - Institute of Electrical and Electronics Engineers Inc., 2018. S. 1048-1052 8451011 (Proceedings - International Conference on Image Processing, ICIP).

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Harvard

De Werneck, RO, Dourado, IC, Fadel, SG, Tabbone, S & Torres, RDS 2018, Graph-Based Early-Fusion for Flood Detection. in 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings., 8451011, Proceedings - International Conference on Image Processing, ICIP, IEEE - Institute of Electrical and Electronics Engineers Inc., S. 1048-1052, 25th IEEE International Conference on Image Processing - ICIP 2018, Athens, Griechenland, 07.10.18. https://doi.org/10.1109/ICIP.2018.8451011

APA

De Werneck, R. O., Dourado, I. C., Fadel, S. G., Tabbone, S., & Torres, R. D. S. (2018). Graph-Based Early-Fusion for Flood Detection. In 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings (S. 1048-1052). Artikel 8451011 (Proceedings - International Conference on Image Processing, ICIP). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIP.2018.8451011

Vancouver

De Werneck RO, Dourado IC, Fadel SG, Tabbone S, Torres RDS. Graph-Based Early-Fusion for Flood Detection. in 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings. IEEE - Institute of Electrical and Electronics Engineers Inc. 2018. S. 1048-1052. 8451011. (Proceedings - International Conference on Image Processing, ICIP). doi: 10.1109/ICIP.2018.8451011

Bibtex

@inbook{d7fb4ffaa42f4bf6aaaf0cacf8359b48,
title = "Graph-Based Early-Fusion for Flood Detection",
abstract = "Flooding is one of the most harmful natural disasters, as it poses danger to both buildings and human lives. Therefore, it is fundamental to monitor these disasters to define prevention strategies and help authorities in damage control. With the wide use of portable devices (e.g., smartphones), there is an increase of the documentation and communication of flood events in social media. However, the use of these data in monitoring systems is not straightforward and depends on the creation of effective recognition strategies. In this paper, we propose a fusion-based recognition system for detecting flooding events in images extracted from social media. We propose two new graph-based early-fusion methods, which consider multiple descriptions and modalities to generate an effective image representation. Our results demonstrate that the proposed methods yield better results than a traditional early-fusion method and a specialized deep neural network fusion solution.",
keywords = "Early fusion, Flood detection, Graph-based fusion, Image representation, MediaEval",
author = "{De Werneck}, {Rafael O.} and Dourado, {Icaro C.} and Fadel, {Samuel G.} and Salvatore Tabbone and Torres, {Ricardo Da S.}",
year = "2018",
month = aug,
day = "29",
doi = "10.1109/ICIP.2018.8451011",
language = "English",
isbn = "978-1-4799-7062-9",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",
pages = "1048--1052",
booktitle = "2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings",
address = "United States",
note = "25th IEEE International Conference on Image Processing - ICIP 2018, ICIP ; Conference date: 07-10-2018 Through 10-10-2018",
url = "https://2018.ieeeicip.org/default.asp",

}

RIS

TY - CHAP

T1 - Graph-Based Early-Fusion for Flood Detection

AU - De Werneck, Rafael O.

AU - Dourado, Icaro C.

AU - Fadel, Samuel G.

AU - Tabbone, Salvatore

AU - Torres, Ricardo Da S.

N1 - Conference code: 25

PY - 2018/8/29

Y1 - 2018/8/29

N2 - Flooding is one of the most harmful natural disasters, as it poses danger to both buildings and human lives. Therefore, it is fundamental to monitor these disasters to define prevention strategies and help authorities in damage control. With the wide use of portable devices (e.g., smartphones), there is an increase of the documentation and communication of flood events in social media. However, the use of these data in monitoring systems is not straightforward and depends on the creation of effective recognition strategies. In this paper, we propose a fusion-based recognition system for detecting flooding events in images extracted from social media. We propose two new graph-based early-fusion methods, which consider multiple descriptions and modalities to generate an effective image representation. Our results demonstrate that the proposed methods yield better results than a traditional early-fusion method and a specialized deep neural network fusion solution.

AB - Flooding is one of the most harmful natural disasters, as it poses danger to both buildings and human lives. Therefore, it is fundamental to monitor these disasters to define prevention strategies and help authorities in damage control. With the wide use of portable devices (e.g., smartphones), there is an increase of the documentation and communication of flood events in social media. However, the use of these data in monitoring systems is not straightforward and depends on the creation of effective recognition strategies. In this paper, we propose a fusion-based recognition system for detecting flooding events in images extracted from social media. We propose two new graph-based early-fusion methods, which consider multiple descriptions and modalities to generate an effective image representation. Our results demonstrate that the proposed methods yield better results than a traditional early-fusion method and a specialized deep neural network fusion solution.

KW - Early fusion

KW - Flood detection

KW - Graph-based fusion

KW - Image representation

KW - MediaEval

UR - http://www.scopus.com/inward/record.url?scp=85062912293&partnerID=8YFLogxK

U2 - 10.1109/ICIP.2018.8451011

DO - 10.1109/ICIP.2018.8451011

M3 - Article in conference proceedings

AN - SCOPUS:85062912293

SN - 978-1-4799-7062-9

T3 - Proceedings - International Conference on Image Processing, ICIP

SP - 1048

EP - 1052

BT - 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th IEEE International Conference on Image Processing - ICIP 2018

Y2 - 7 October 2018 through 10 October 2018

ER -

DOI

Zuletzt angesehen

Publikationen

  1. Development and prospects of degradable magnesium alloys for structural and functional applications in the fields of environment and energy
  2. Belief in free will affects causal attributions when judging others’ behavior
  3. A switching observer for sensorless control of an electromagnetic valve actuator for camless internal combustion engines
  4. What is intergovernmental about the EU’s ‘(new) intergovernmentalist’ turn? Evidence from the Eurozone and asylum crises
  5. How context affects transdisciplinary research
  6. »CO2 causes a hole in the atmosphere« Using laypeople’s conceptions as a starting point to communicate climate change
  7. From 'one right way' to 'one ruinous way'? Discursive shifts in 'There is no alternative'
  8. Material system analysis
  9. Social group membership does not modulate automatic imitation in a contrastive multi-agent paradigm
  10. System and action theory
  11. Inter- and intraspecific consumer trait variations determine consumer diversity effects in multispecies predator−prey systems
  12. Anisotropic wavelet bases and thresholding
  13. Formalised and Non-Formalised Methods in Resource Management-Knowledge and Social Learning in Participatory Processes
  14. Developing a die casting magnesium alloy with excellent mechanical performance by controlling intermetallic phase
  15. An analysis of the requirements for DSS on integrated river basin management
  16. Proof of concept
  17. Effects of different video- or text-based reflection stimuli on pre-service teachers’ emotions, immersion, cognitive load and knowledge-based reasoning
  18. Modality in Nigerian Senate Debates: Patterned co-occurrence and stratgic-pragmatic functions
  19. Similarity of molecular descriptors: The equivalence of Zagreb indices and walk counts
  20. What workers want: job satisfaction in the U.S.
  21. Repatriation, Public Programming, and the DEAI Toolkit
  22. Does Job Satisfaction Adapt to Working Conditions?
  23. The Continuities of Twitter Strategies and Algorithmic Terror
  24. Development perspectives for the application of autonomous, unmanned aerial systems (UASs) in wildlife conservation
  25. Odor Classification
  26. Anonymized Firm Data under Test: Evidence from a Replication Study
  27. Numerical approach for the evaluation of seam welding criteria in extrusion processes
  28. Effects of tree diversity on canopy space occupation vary with tree size and canopy space definition in a mature broad-leaved forest
  29. TALIS (GEW)
  30. Investigation of the deformation behavior of Fe-3%Si sheet metal with large grains via crystal plasticity and finite-element modeling
  31. Dynamic Capabilities in Sustainable Supply Chain Management
  32. Das fossile Imperium schlägt zurück
  33. Not only biocidal products
  34. Treating the nestedness temperature calculator as a "black box" can lead to false conclusions
  35. Time use and time budgets
  36. A comparative survey of chemistry-driven in silico methods to identify hazardous substances under REACH