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From:
Bogdan Ionescu <[log in to unmask]>
Reply To:
Bogdan Ionescu <[log in to unmask]>
Date:
Tue, 18 Jan 2022 23:51:15 +0200
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[Apologies for multiple postings]

ImageCLEF 2022
Multimedia Retrieval in CLEF
http://www.imageclef.org/2022/
https://www.facebook.com/ImageClef/
https://twitter.com/imageclef/


*** CALL FOR PARTICIPATION ***

ImageCLEF 2022 is an evaluation campaign that is being organized as
part of the CLEF (Conference and Labs of the Evaluation Forum) labs.
The campaign offers several research tasks that welcome participation
from teams around the world.

The results of the campaign appear in the working notes proceedings,
published by CEUR Workshop Proceedings (CEUR-WS.org) and are presented
in the CLEF conference. Selected contributions among the participants
will be invited for submission to a special section "Best of CLEF'21
Labs" in the Springer Lecture Notes in Computer Science (LNCS) of
CLEF'22, together with the annual lab overviews.

Target communities involve (but are not limited to):
- information retrieval (text, vision, audio, multimedia, social
media, sensor data, etc.)
- machine learning, deep learning
- data mining
- natural language processing
- image and video processing
- computer vision
with special attention to the challenges of multi-modality,
multi-linguality, and interactive search.


*** 2022 TASKS ***

*ImageCLEFcoral* (4th edition)
https://www.imageclef.org/2022/coral
The increasing use of structure-from-motion photogrammetry for
modelling large-scale environments from action cameras attached to
drones has driven the next-generation of visualisation techniques that
can be used in augmented and virtual reality headsets. The task
addresses this particular issue for monitoring coral reef structure
and composition, in support of their conservation.

Organizers: Jon Chamberlain, Adrian Clark, and Alba García Seco de
Herrera (University of Essex, UK), and Antonio Campello (Wellcome
Trust, UK).

*ImageCLEFmedical* (4th edition)
https://www.imageclef.org/2022/medical
Medical images can be used in a variety of scenarios and this task
will combine the most popular medical tasks of ImageCLEF and continue
the idea of 2020 by mixing various applications, namely: (i) automatic
image captioning with medical visual question
answering, and (ii) analysis of tuberculosis patients by finding
cavities where the disease possibly remains even after a first
treatment.

Organizers: Johannes Rückert, Christoph M. Friedrich, Louise Bloch,
Raphael Brüngel, Ahmad Idrissi-Yaghir, and Henning Schäfer (University
of Applied Sciences and Arts Dortmund, Germany), Asma Ben Abacha
(National Library of Medicine, USA), Alba García Seco de Herrera
(University of Essex, UK), Henning Müller (University of Applied
Sciences Western Switzerland, Sierre, Switzerland), Serge Kozlovski,
Vitali Liauchuk, and Vassili Kovalev (Institute for Informatics,
Minsk, Belarus), and Yashin Dicente Cid (University of Warwick,
Coventry, England, UK).

*ImageCLEFaware2022* (2nd edition)
https://www.imageclef.org/2022/aware
The images available on social networks can be exploited in ways users
are unaware of when initially shared, including situations that have
serious consequences for the users’ real lives. For instance, it is
common practice for prospective employers to search online for
information about their future employees. This task addresses the
development of algorithms which raise the users’ awareness about
real-life impact of online image sharing.

Organizers: Adrian Popescu, Jérôme Deshayes-Chossart, and Hugo
Schindler (CEA LIST, France), and Bogdan Ionescu (Politehnica
University of Bucharest, Romania).

*ImageCLEFfusion2022* (new)
https://www.imageclef.org/2022/fusion
Despite the current advances in knowledge discovery, single learners
do not produce satisfactory performance when dealing with complex
data, such as class imbalance, high-dimensionality, concept drift,
noisy data, multimodal data, etc. The task aims to fill this gap by
exploiting novel and innovative late fusion techniques for producing a
powerful learner based on the expertise of the pool of classifiers it
integrates. The task requires participants to develop aggregation
mechanisms of the outputs of the supplied systems and generate
ensemble predictions with significantly higher performance than the
individual systems.

Organizers: Liviu-Daniel Stefan, Mihai Gabriel Constantin, Mihai
Dogariu, and Bogdan Ionescu (Politehnica University of Bucharest,
Romania).


*** IMPORTANT DATES ***
(may vary depending on the task)
- Task registration opens: November 15, 2021
- Run submission: May 6, 2022
- Working notes submission: May 27, 2022
- CLEF 2022 conference: September 5-8, Bologna, Italy


*** REGISTRATION ***
Follow the instructions here https://www.imageclef.org/2022.


*** OVERALL COORDINATION ***
Bogdan Ionescu, Politehnica University of Bucharest, Romania
Henning Müller, HES-SO, Sierre, Switzerland
Renaud Péteri, University of La Rochelle, France


On behalf of the organizers,

Bogdan Ionescu
https://www.aimultimedialab.ro/

############################

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