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Report on the 2025 IEEE GRSS Data Fusion Contest: All-Weather Land Cover and Building Damage Mapping [Technical Committees]

  • Claudio Persello
  • , Ujjwal Verma*
  • , Saurabh Prasad
  • , Gemine Vivone
  • , Hongruixuan Chen
  • , Junshi Xia
  • , Jian Song
  • , Clifford Broni-Bediako
  • , Olivier Dietrich
  • , Konrad Schindler
  • , Naoto Yokoya
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Over the past two decades, the annual Data Fusion Contest (DFC) has emerged as a platform that invites researchers worldwide to advance data fusion and image analysis methodologies. The contest focuses on the challenges of handling large-scale, multisensor, multimodal, and multitemporal data, fostering innovation in remote sensing research. The past editions have introduced novel and demanding problem settings, thereby creating benchmarks that have shaped progress in the field. The contest has been hosted annually since 2006 by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]. This year’s contest focus was allweather land cover and building damage mapping.

Original languageEnglish
Pages (from-to)488-492
Number of pages5
JournalIEEE Geoscience and Remote Sensing Magazine
Volume13
Issue number4
DOIs
Publication statusPublished - 2025

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Instrumentation
  • Electrical and Electronic Engineering
  • General Earth and Planetary Sciences

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