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Overview of the imageCLEF 2022: Multimedia Retrieval in Medical, Social Media and Nature Applications 13th

Overview of the ImageCLEF 2022: Multimedia Retrieval in Medi...

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13th International Conference of the CLEF-Association (CLEF) - Experimental IR meets Multilinguality, Multimodality, and Interaction

作者： Ionescu, Bogdan Muller, Henning Peteri, Renaud Ruckert, Johannes Ben Abacha, Asma de Herrera, Alba G. Seco Friedrich, Christoph M. Bloch, Louise Brungel, Raphael Idrissi-Yaghir, Ahmad Schafer, Henning Kozlovski, Serge Cid, Yashin Dicente Kovalev, Vassili Stefan, Liviu-Daniel Constantin, Mihai Gabriel Dogariu, Mihai Popescu, Adrian Deshayes-Chossart, Jerome Schindler, Hugo Chamberlain, Jon Campello, Antonio Clark, Adrian Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Sierre Switzerland Univ La Rochelle La Rochelle France Univ Appl Sci & Arts Dortmund Dortmund Germany Microsoft Redmond WA USA Univ Essex Colchester Essex England Inst Informat Minsk BELARUS Univ Warwick Coventry W Midlands England Univ Paris Saclay LIST CEA F-91120 Palaiseau France Wellcome Trust Res Labs London England

ISBN: (纸本)9783031136436;9783031136429

This paper presents an overview of the imageCLEF 2022 lab that was organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2022. imageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2022, the 20th edition of imageCLEF runs four main tasks: (i) a medical task that groups two previous tasks, i.e., caption analysis and tuberculosis prediction, (ii) a social media aware task on estimating potential real-life effects of online image sharing, (iii) a nature coral task about segmenting and labeling collections of coral reef images, and (iv) a new fusion task addressing the design of late fusion schemes for boosting the performance, with two real-world applications: image search diversification (retrieval) and prediction of visual interestingness (regression). The benchmark campaign received the participation of over 25 groups submitting more than 258 runs.

关键词： Medical image classification medical image caption analysis tuberculosis prediction coral image segmentation and classification prediction of effects of online image sharing late fusion for search diversification and interestingness prediction imageCLEF lab

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Overview of the imageCLEF 2021: Multimedia Retrieval in Medical, Nature, Internet and Social Media Applications 12th

Overview of the ImageCLEF 2021: Multimedia Retrieval in Medi...

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12th International Conference of the CLEF Association (CLEF)

作者： Ionescu, Bogdan Muller, Henning Peteri, Renaud Ben Abacha, Asma Sarrouti, Mourad Demner-Fushman, Dina Hasan, Sadid A. Kozlovski, Serge Liauchuk, Vitali Cid, Yashin Dicente Kovalev, Vassili Pelka, Obioma de Herrera, Alba Garcia Seco Jacutprakart, Janadhip Friedrich, Christoph M. Berari, Raul Tauteanu, Andrei Fichou, Dimitri Brie, Paul Dogariu, Mihai Stefan, Liviu Daniel Constantin, Mihai Gabriel Chamberlain, Jon Campello, Antonio Clark, Adrian Oliver, Thomas A. Moustahfid, Hassan Popescu, Adrian Deshayes-Chossart, Jerome Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Delemont Switzerland Univ La Rochelle La Rochelle France Natl Lib Med Bethesda MD USA CVS Hlth Wellesley MA USA United Inst Informat Problems Minsk BELARUS Univ Warwick Coventry W Midlands England Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Essex Colchester Essex England TeleportHQ Cluj Napoca Romania Wellcome Trust Res Labs London England Pacific Isl Fisheries Sci Ctr Silver Spring MD USA Univ Paris Saclay List CEA Palaiseau France

ISBN: (纸本)9783030852504;9783030852511

This paper presents an overview of the imageCLEF 2021 lab that was organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2021. imageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2021, the 19th edition of imageCLEF runs four main tasks: (i) a medical task that groups three previous tasks, i.e., caption analysis, tuberculosis prediction, and medical visual question answering and question generation, (ii) a nature coral task about segmenting and labeling collections of coral reef images, (iii) an Internet task addressing the problems of identifying hand-drawn and digital user interface components, and (iv) a new social media aware task on estimating potential real-life effects of online image sharing. Despite the current pandemic situation, the benchmark campaign received a strong participation with over 38 groups submitting more than 250 runs.

关键词： Visual question answering and generation Medical image classification coral image segmentation and classification Recognition of website user interface components Prediction of effects of online image sharing imageCLEF lab

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Overview of the imageCLEF 2020: Multimedia Retrieval in Medical, Lifelogging, Nature, and Internet Applications 1

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11th International Conference of the CLEF Association (CLEF)

作者： Ionescu, Bogdan Muller, Henning Peteri, Renaud Ben Abacha, Asma Datla, Vivek Hasan, Sadid A. Demner-Fushman, Dina Kozlovski, Serge Liauchuk, Vitali Cid, Yashin Dicente Kovalev, Vassili Pelka, Obioma Friedrich, Christoph M. de Herrera, Alba Garcia Seco Van-Tu Ninh Tu-Khiem Le Zhou, Liting Piras, Luca Riegler, Michael Halvorsen, Pal Minh-Triet Tran Lux, Mathias Gurrin, Cathal Duc-Tien Dang-Nguyen Chamberlain, Jon Clark, Adrian Campello, Antonio Fichou, Dimitri Berari, Raul Brie, Paul Dogariu, Mihai Stefan, Liviu Daniel Constantin, Mihai Gabriel Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Sierre Switzerland Univ La Rochelle La Rochelle France Natl Lib Med Bethesda MD USA Philips Res Cambridge Cambridge MA 02141 USA CVS Hlth Monroeville PA 15146 USA United Inst Informat Problems Minsk BELARUS Univ Warwick Coventry W Midlands England Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Essex Colchester Essex England Dublin City Univ Dublin Ireland Pluribus One Cagliari Italy Univ Cagliari Cagliari Italy Univ Oslo Oslo Norway Univ Sci Ho Chi Minh City Vietnam Klagenfurt Univ Klagenfurt Austria Univ Bergen Bergen Norway Wellcome Trust Res Labs London England TeleportHQ Cluj Napoca Romania

ISBN: (数字)9783030582197

ISBN: (纸本)9783030582180;9783030582197

This paper presents an overview of the imageCLEF 2020 lab that was organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2020. imageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2020, the 18th edition of imageCLEF runs four main tasks: (i) a medical task that groups three previous tasks, i.e., caption analysis, tuberculosis prediction, and medical visual question answering and question generation, (ii) a lifelog task (videos, images and other sources) about daily activity understanding, retrieval and summarization, (iii) a coral task about segmenting and labeling collections of coral reef images, and (iv) a new Internet task addressing the problems of identifying hand-drawn user interface components. Despite the current pandemic situation, the benchmark campaign received a strong participation with over 40 groups submitting more than 295 runs.

关键词： Visual question answering Visual question generation Lifelogging retrieval and summarization Medical image classification coral image segmentation and classification Recognition of hand-drawn website user interface components imageCLEF benchmark Annotated data Common evaluation framework

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imageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications 42nd

ImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical...

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42nd European Conference on IR Research

作者： Ionescu, Bogdan Muller, Henning Peteri, Renaud Duc-Tien Dang-Nguyen Zhou, Liting Piras, Luca Riegler, Michael Halvorsen, Pal Tran, Minh-Triet Lux, Mathias Gurrin, Cathal Chamberlain, Jon Clark, Adrian Campello, Antonio de Herrera, Alba G. Seco Ben Abacha, Asma Datla, Vivek Hasan, Sadid A. Liu, Joey Demner-Fushman, Dina Pelka, Obioma Friedrich, Christoph M. Cid, Yashin Dicente Kozlovski, Serge Liauchuk, Vitali Kovalev, Vassili Berari, Raul Brie, Paul Fichou, Dimitri Dogariu, Mihai Stefan, Liviu Daniel Constantin, Mihai Gabriel Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Delemont Switzerland Univ La Rochelle La Rochelle France Univ Bergen Bergen Norway Dublin City Univ Dublin Ireland Pluribus One Cagliari Italy Univ Cagliari Cagliari Italy SimulaMet Oslo Norway Univ Sci Ho Chi Minh City Vietnam Klagenfurt Univ Klagenfurt Austria Univ Essex Colchester Essex England Wellcome Trust Res Labs London England Natl Lib Med Bethesda MD USA Philips Res Cambridge Cambridge MA USA CVS Hlth Monroeville PA USA Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Warwick Coventry W Midlands England United Inst Informat Problems Minsk BELARUS teleportHQ Cluj Napoca Romania

ISBN: (纸本)9783030454418;9783030454425

This paper presents an overview of the 2020 imageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum-CLEF Labs 2020 in Thessaloniki, Greece. imageCLEF is an ongoing evaluation initiative (run since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2020, the 18th edition of imageCLEF will organize four main tasks: (i) a Lifelog task (videos, images and other sources) about daily activity understanding, retrieval and summarization, (ii) a Medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data and adapted tasks, (iii) a coral task about segmenting and labeling collections of coral images for 3D modeling, and a new (iv) Web user interface task addressing the problems of detecting and recognizing hand drawn website UIs (User Interfaces) for generating automatic code. The strong participation, with over 235 research groups registering and 63 submitting over 359 runs for the tasks in 2019 shows an important interest in this benchmarking campaign. We expect the new tasks to attract at least as many researchers for 2020.

关键词： Lifelogging retrieval and summarization Medical image classification coral image segmentation and classification Recognition of hand drawn website UIs imageCLEF benchmarking Annotated data

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imageCLEF 2019: Multimedia Retrieval in Medicine, Lifelogging, Security and Nature 1

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10th International Conference of the CLEF-Association (CLEF)

作者： Ionescu, Bogdan Mueller, Henning Peteri, Renaud Cid, Yashin Dicente Liauchuk, Vitali Kovalev, Vassili Klimuk, Dzmitri Tarasau, Aleh Ben Abacha, Asma Hasan, Sadid A. Datla, Vivek Liu, Joey Demner-Fushman, Dina Duc-Tien Dang-Nguyen Piras, Luca Riegler, Michael Minh-Triet Tran Lux, Mathias Gurrin, Cathal Pelka, Obioma Friedrich, Christoph M. de Herrera, Alba Garcia Seco Garcia, Narciso Kavallieratou, Ergina del Blanco, Carlos Roberto Cuevas, Carlos Vasillopoulos, Nikos Karampidis, Konstantinos Chamberlain, Jon Clark, Adrian Campello, Antonio Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Sierre Switzerland La Rochelle Univ La Rochelle France Dublin City Univ Dublin Ireland Pluribus One Cagliari Italy Univ Cagliari Cagliari Italy Univ Oslo Oslo Norway Univ Sci Ho Chi Minh City Vietnam Klagenfurt Univ Klagenfurt Austria Inst Informat Minsk BELARUS Philips Res Cambridge Cambridge MA USA Natl Lib Med Bethesda MD USA Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Essex Colchester Essex England ETS Ingn Telecomunicac Madrid Spain Univ Aegean Mitilini Greece Univ Bergen Bergen Norway Republican Res & Pract Ctr Pulmonol & TB Minsk BELARUS Filament London England

ISBN: (数字)9783030285777

ISBN: (纸本)9783030285777;9783030285760

This paper presents an overview of the imageCLEF 2019 lab, organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2019. imageCLEF is an ongoing evaluation initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2019, the 17th edition of imageCLEF runs four main tasks: (i) a medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data, (ii) a lifelog task (videos, images and other sources) about daily activities understanding, retrieval and summarization, (iii) a new security task addressing the problems of automatically identifying forged content and retrieve hidden information, and (iv) a new coral task about segmenting and labeling collections of coral images for 3D modeling. The strong participation, with 235 research groups registering, and 63 submitting over 359 runs, shows an important interest in this benchmark campaign.

关键词： Medical retrieval Life logging retrieval and summarization File Forgery Detection coral image segmentation and classification imageCLEF benchmarking Annotated data sets

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