[Apologies for multiple postings] ImageCLEFfusion https://www.imageclef.org/2022/fusion *** CALL FOR PARTICIPATION *** While deep neural networks have proven their predictive power in many tasks, there are still several domains where a single deep learning network is not enough for attaining high precision, e.g., prediction of subjective concepts such as violence, memorability, etc. Late fusion, also called ensembling or decision-level fusion, represents one of the approaches that researchers employ to increase the performance of single-system approaches. It consists of using a series of weaker learner methods called inducers, whose prediction outputs are combined in the final step, via a fusion mechanism to create a new and improved super predictor. These systems have a long history and are shown to be particularly useful in scenarios where the performance of single-system approaches is not considered satisfactory. The task challenge participants to develop and benchmark late fusion schemes. This task would allow to explore various aspects of late fusion mechanisms, such as the performance of different fusion methods, the methods for selecting inducers from a larger set, the exploitation of positive and negative correlations between inducers, and so on. *** TASK *** The participants will receive a data set of real inducers and are expected to provide a fusion mechanism that would allow to combine them into a super-system yielding superior performance compared to the highest performing individual system. The provided inducers were developed to solve two real tasks: (i) prediction of visual interestingness (int), and (ii) diversification of image search results (div). *** DATA SET *** ImageCLEFfusion-int. The data for this task is extracted and corresponds to the Interestingness10k dataset. We provide output data from 33 inducers, representing visual interestingness predictions for 2,435 images. ImageCLEFfusion-div. The data for this task is extracted and corresponds to the Retrieving Diverse Social Images Task dataset. We provide outputs from 56 inducers, representing a total of 123 queries. *** METRICS *** Evaluation will be performed using the metrics specific to each dataset we use, i.e., MAP@10 for the interestingness prediction, and F1@20 and ClusterRecall@20 for the search results diversification. *** IMPORTANT DATES *** - 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 *** REGISTER *** https://www.imageclef.org/2022#registration *** OVERALL COORDINATION *** Liviu-Daniel Stefan, Politehnica University of Bucharest, Romania Mihai Gabriel Constantin, Politehnica University of Bucharest, Romania Mihai Dogariu, Politehnica University of Bucharest, Romania Bogdan Ionescu, Politehnica University of Bucharest, Romania On behalf of the Organizers, Bogdan Ionescu https://www.AIMultimediaLab.ro/ ############################ Unsubscribe: [log in to unmask] If you don't already have a password for the LISTSERV.ACM.ORG server, we recommend that you create one now. A LISTSERV password is linked to your email address and can be used to access the web interface and all the lists to which you are subscribed on the LISTSERV.ACM.ORG server. To create a password, visit: https://LISTSERV.ACM.ORG/SCRIPTS/WA-ACMLPX.CGI?GETPW1 Once you have created a password, you can log in and view or change your subscription settings at: https://LISTSERV.ACM.ORG/SCRIPTS/WA-ACMLPX.CGI?SUBED1=MM-INTEREST