ICIAP 2023 - 22nd International Conference on Image Analysis and Processing https://www.iciap2023.org CALL TUTORIALS The 22nd International Conference on Image Analysis And Processing (ICIAP 2023) to be held in Udine, Italy will host tutorials on topics related to research in Computer Vision, Machine Learning, Image Processing, Medical Imaging and related fields. Tutorial topics should be relevant to the current state of the art in the research area of interest and provide surveys and new perspectives to current trends. Tutorials will take place on September 11 and 15, 2023 with both half (max 4 hours) and full day (max 8 hours) options. Attendance will mainly consist of graduated students and experts in the field from both academic and industry sectors. IMPORTANT DATES - Tutorial proposal deadline 07 April 2023 - Acceptance notification 01 May 2023 INSTRUCTIONS Tutorial proposals should be submitted via google forms: https://forms.gle/rMrUnzs85umrcEFj7 and should include all the following information: - Proposed title - Proposers' names, titles, affiliations, emails, brief bio sketches and photos - Preference for half- or full-day event (the latter requires a brief justification) - An abstract of the tutorial (max 1500 characters) - Tutorial description with a syllabus of the topics to be covered (max 5000 characters) - Previous experience in tutorial organization (provide links if available) - Links to a few recorded talks given by the presenters (if available) - Description of and/or links to any planned materials or resources to be distributed to attendees The proposals will be evaluated by the tutorial chairs and the conference organizer based on their technical quality, relevance and timeliness of the topic and quality of the proposal. CONTACTS For any further information please contact tutorials@iciap2023.org
ICIAP 2023 – Call for Tutorials
February 21st, 2023 
Daniela Lopez de Luise 11th International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM) @ IEEE ICASSP 2023 | Rhodes Island, Greece | June 4-9, 2023
February 21st, 2023 Daniela Lopez de Luise We cordially invite you to submit your original contributions to IWCIM 2023 – the 11th International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), which will take place as a satellite workshop to IEEE ICASSP 2023, to be held in Rhodes Island, Greece on June 4 – 9, 2023.
Please see the workshop website https://iwcim.itu.edu.tr/ and the general conference web page https://2023.ieeeicassp.org/ for more information.
IWCIM 2023 is the annual workshop organized by the working group Multimedia Understanding through Semantics, Computation and Learning (MUSCLE) of the European Research Consortium for Informatics and Mathematics (ERCIM).
Multimedia understanding is an important part of many intelligent applications in our social life, whether in our households or in commercial, industrial, service, and scientific environments. Analyzing raw data to provide them with semantics is essential to exploit their full potential and help us manage our everyday tasks. Nowadays, raw data normally come from a host of different sensors and other sources and are different in nature, format, reliability and information content. Multimodal and cross-modal analysis are the only ways to use them at their best. Besides data analysis, this problem is also relevant to data description intended to help storage and mining. Interoperability and exchangeability of heterogeneous and distributed data is a need for any practical application. Semantics is information at the highest level, and inferring it from raw data (that is, from information at the lowest level) entails exploiting both data and prior information to extract structure and meaning. Computation, machine learning, statistical and Bayesian methods are tools to achieve this goal at various levels.
Multimedia understanding is an important part of many intelligent applications in our social life, whether in our households or in commercial, industrial, service, and scientific environments. Analyzing raw data to provide them with semantics is essential to exploit their full potential and help us manage our everyday tasks. Nowadays, raw data normally come from a host of different sensors and other sources and are different in nature, format, reliability and information content. Multimodal and cross-modal analysis are the only ways to use them at their best. Besides data analysis, this problem is also relevant to data description intended to help storage and mining. Interoperability and exchangeability of heterogeneous and distributed data is a need for any practical application. Semantics is information at the highest level, and inferring it from raw data (that is, from information at the lowest level) entails exploiting both data and prior information to extract structure and meaning. Computation, machine learning, statistical and Bayesian methods are tools to achieve this goal at various levels.
TOPICS:
The scope of IWCIM 2023 includes, but is not limited to the following topics:
o Multisensor systems
o Multimodal analysis
o Crossmodal data analysis and clustering
o Mixed-reality applications
o Activity and object detection/recognition
o Text and speech recognition
o Multimedia labeling, semantic annotation, and metadata
o Multimodal indexing and searching in very large data-bases
o Big and Linked Data Search and mining Big Data
o Large-scale recommendation systems
o Multimedia and Multi-structured data
o Semantic web and Linked Data
o Cloud Optimization
o Pervasive Intelligence
o Machine learning in multimedia understanding
o Attention-based approaches for multimedia understanding
o Diffusion models for multi-modal data analysis
o Multi-modal data analysis in compressed domain
o Multi-modal data analysis for remote sensing applications
o Semantic web and Linked data
o Case studies
PUBLICATION:
All the papers accepted for the workshop will be included in the conference proceedings published in IEEExplore.
SUBMISSION:
All contributions should be original and not published elsewhere or intended to be published during the review period.
Authors who wish to participate in the conference will create documents consisting of a complete description of their ideas and applicable research results in a maximum of 4 pages for technical content, including figures and possible references, and with one additional optional 5th page containing only references.
Papers should be submitted through the ICASSP 2023 submission website using Microsoft’s Conference Management Toolkit (CMT): https://cmt3.research.microsoft.com/ICASSP2023/Submission/Index
When submitting, please be sure to select the track “Satellite Workshop: IWCIM 2023: The Eleventh International Workshop on Computational Intelligence for Multimedia Understanding”.
Templates for preparing the manuscript in Latex and MS Word are available here: https://2023.ieeeicassp.org/paper-submission-guidelines/
DATES:
Submission of papers:February 24, 2023 March 14, 2023
Notification of acceptance: April 14, 2023
Camera-ready papers: April 28, 2023
Workshop date: June 5 (To be confirmed)
Submission of papers:
Notification of acceptance: April 14, 2023
Camera-ready papers: April 28, 2023
Workshop date: June 5 (To be confirmed)
– Workshop Organizers –
Behçet Uğur Töreyin, Informatics Institute, Istanbul Technical University (ITU), Istanbul, Turkey
Maria Trocan, Institut Supérieur d'Électronique de Paris (ISEP), Paris, France
Davide Moroni, Institute of Information Science and Technologies, National Research Council of Italy (CNR), Pisa, Italy
Special session on AI and physical models at the next CBMI conference, deadline April 12
February 21st, 2023 Daniela Lopez de Luise ;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;background-color:rgb(253,252,250)”>
we organize in France the next international conference CBMI2023. It will be held in Orleans at the end of September.
A special session is proposed on AI and physical models. We have already organized special sessions of this type at CBMI, on specialized themes such as astrophysics, remote sensing, etc., for which the methodologies are very complementary to what we find in the multimedia domain, the historical axis of CBMI. This association of fields creates an interesting emulation in the community.
Please find the call bellow and do not hesitate to distribute to your interested colleagues.
Welcome at CBMI2023 in Orléans !
special session on : Physical Models and AI in Image and in Multimodality at CBMI2023 conference (http://cbmi2023.org/)
Paper submission deadline is April 12
Deep neural networks now enable the learning of complex functions from the data to address a variety of difficult problems. However, questions emerge on the relevance and understanding of their learned functions, especially when relating to physical models.
Knowledge on the physical environment can allow for the introduction of constraints on the model in order to reduce the search space and to converge to more relevant and simplified solutions that can contribute to higher model confidence. Image synthesis and computer graphics are typical application domains that make use of the known physical constraints on objects and materials to produce realistic images.
Conversely, when the physical model is not perfectly known, AI-based models can help identify relevant solutions to improve the physicist's knowledge and understanding of a given phenomenon. A typical example is haze removal in images while the physical haze model is still not well identified.
Finally, when addressing AI and physics problems, the different data modalities need to be fused appropriately. Again, multimodality handling can be guided by knowledge on the physical model or can be learnt in order to increase knowledge.
This special session aims to bring together researchers working on analysis, indexing, and mining of data related to images and multimodality in various fields involving physical models, remote sensing, astrophysics, mechanics, computer graphics, provides them a venue for sharing novel ideas and discuss their most recent works and promotes exchanges between computer scientists and astrophysicists. Topics of interest include (but are not limited to):
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Supervised learning: classification and regression
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Unsupervised learning: clustering and dimensionality reduction
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Real time, on-site or on-board processing
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Learning physical models from data
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From simulated to actual data
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Time-Series Analysis
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Management of data in physics
Organizer :
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Alexandre Benoit, Savoie Mont Blanc University, LISTIC, Annecy, France — alexandre.benoit@univ-smb.fr
Alexandre BENOIT, Computer Science Professor
Image&signal understanding, Machine Learning, Deep Learning
LISTIC Lab / Polytech Annecy-Chambéry, FRANCE
https://www.univ-smb.fr/listic/en/presentation_listic/membres/enseignants-chercheurs/alexandre-benoit/
Image&signal understanding, Machine Learning, Deep Learning
LISTIC Lab / Polytech Annecy-Chambéry, FRANCE
https://www.univ-smb.fr/listic/en/presentation_listic/membres/enseignants-chercheurs/alexandre-benoit/
