[Corpora-List] Call-for-Participation: ImageCLEF 2022 Tasks

Bogdan Ionescu bogdanlapi at gmail.com
Tue Jan 18 22:51:35 CET 2022


[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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