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ICDAR'22: Intelligent Cross-Data Analysis and Retrieval

Published: 27 June 2022 Publication History

Abstract

We have witnessed the rise of cross-data against multimodal data problems recently. The cross-modal retrieval system uses a textual query to look for images; the air quality index can be predicted using lifelogging images; the congestion can be predicted using weather and tweets data; daily exercises and meals can help to predict the sleeping quality are some examples of this research direction. Although vast investigations focusing on multimodal data analytics have been developed, few cross-data (e.g., cross-modal data, cross-domain, cross-platform) research has been carried on. In order to promote intelligent cross-data analytics and retrieval research and to bring a smart, sustainable society to human beings, the specific article collection on "Intelligent Cross-Data Analysis and Retrieval" is introduced. This Research Topic welcomes those who come from diverse research domains and disciplines such as well-being, disaster prevention and mitigation, mobility, climate change, tourism, healthcare, and food computing

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  • (2023)Multiverse: Multilingual Evidence for Fake News DetectionJournal of Imaging10.3390/jimaging90400779:4(77)Online publication date: 27-Mar-2023

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cover image ACM Conferences
ICMR '22: Proceedings of the 2022 International Conference on Multimedia Retrieval
June 2022
714 pages
ISBN:9781450392389
DOI:10.1145/3512527
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 June 2022

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Author Tags

  1. cross-data analysis
  2. cross-modal models
  3. federated learning
  4. hidden knowledge reveal
  5. image clustering and segmentation
  6. prediction model
  7. privacy-preserving
  8. social multimedia
  9. time-series data forecast
  10. transformer

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ICMR '22
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Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

View all
  • (2023)Multiverse: Multilingual Evidence for Fake News DetectionJournal of Imaging10.3390/jimaging90400779:4(77)Online publication date: 27-Mar-2023

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