CFP – IET Image Processing special issue on “Advancements in Fine Art Pattern Extraction and Recognition” [deadline 28 November 2022]

*Call for Papers*

_______ *Special Issue of IET Image Processing on* __________
*ADVANCEMENTS in FINE ART PATTERN EXTRACTION and RECOGNITION*

___________
Aim & Scope

Cultural heritage, especially fine arts, plays an invaluable role in the
cultural, historical and economic growth of our societies. Fine arts are
primarily developed for aesthetic purposes and are mainly expressed
through painting, sculpture and architecture. In recent years, thanks to
technological improvements and drastic cost reductions, a large-scale
digitization effort has been made, which has led to an increasing
availability of large digitized fine art collections. This availability,
coupled with recent advances in pattern recognition and computer vision,
has disclosed new opportunities, especially for researchers in these
fields, to assist the art community with automatic tools to further
analyze and understand fine arts. Among other benefits, a deeper
understanding of fine arts has the potential to make them more
accessible to a wider population, both in terms of fruition and
creation, thus supporting the spread of culture.

This special issue aims to offer the opportunity to present advancements
in the state-of-the-art, innovative research, ongoing projects, and
academic and industrial reports on the application of visual pattern
extraction and recognition for a better understanding and fruition of
fine arts, soliciting contributions from pattern recognition, computer
vision, artificial intelligence and image processing research areas. The
special issue will be linked to the 2nd International Workshop on Fine
Art Pattern Extraction and Recognition (FAPER2022). Authors of selected
conference papers will be invited to extend and improve their
contributions for this special issue, and authors are also invited to
submit new contributions (non-conference papers).

_______________________________________
Topics include, but are not limited to:
– Applications of machine learning and deep learning to cultural
heritage and digital humanities
– Computer vision and multimedia data processing for fine arts
– Generative adversarial networks for artistic data
– Augmented and virtual reality for cultural heritage
– 3D reconstruction of historical artifacts
– Point cloud segmentation and classification for cultural heritage
– Historical document analysis
– Content-based retrieval in visual art domain
– Digitally enriched museum visits
– Smart interactive experiences in cultural sites
– Project, products or prototypes for cultural heritage

_______________________________________
*Submission Deadline*: 28 November 2022

Submissions must be made through ScholarOne:
https://mc.manuscriptcentral.com/theiet-ipr

see the PDF call for paper for more information:
https://ietresearch.onlinelibrary.wiley.com/pb-assets/assets/17519667/Special%20Issues/IPR%20SI%20CFP_AFAPER-1651107571727.pdf

___________
Open Access

 From January 2021, The IET began an Open Access publishing partnership
with Wiley. As a result, all submissions that are accepted for this
Special Issue will be published under the Gold Open Access Model and
subject to the Article Processing Charge (APC) of $2,300.

APC can be covered in *FULL* or part by your institution!
*CHECK  YOUR  ELIGIBILITY  HERE*
https://authorservices.wiley.com/author-resources/Journal-Authors/open-access/affiliation-policies-payments/institutional-funder-payments.html

_______________
Editor-in-Chief

Prof. Farzin Deravi, University of Kent, UK

_____________
Guest Editors

Giovanna Castellano, Universita' di Bari, Italy
Gennaro Vessio, Universita' di Bari, Italy
Fabio Bellavia, Universita' di Palermo, Italy
Sinem Aslan, Università Ca' Forscari Venezia, Italy

Call for papers – IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (J-STSP)


IEEE JOURNAL OF SELECTED TOPICS


IN SIGNAL PROCESSING (J-STSP)


 


 Special issue on “Biometrics at a distance in the Deep Learning era


 


 


Call for papers


Biometrics at a distance (e.g., gait recognition, person re-identification, etc.) is a particular case of biometric analysis that usually does not require the conscious participation of the target subject, being non-invasive at the same time. However, the sample acquisition is almost always affected by adverse conditions, e.g., the lack of details due to the distance itself, so that the robustness to distortions of adopted biometric methods is of paramount importance. This is a well-established topic in the field of information forensics and security. With the arrival of the Deep Learning era, new approaches have started to emerge in dealing with this task. However, in contrast to other computer vision and machine learning problems, as general image/video classification, one of the main challenges that has to be addressed in this type of biometric problem, amongst others, is the lack or limited amount of available annotated data sets for effectively training deep models.


The aim of this special issue is to gather and promote novel deep-learning based approaches for addressing the task of biometrics at a distance. Specifically, we are interested in works that propose new methods to improve the recognition accuracy, the computational burden and/or the scalability of the domain of application for biometrics, being the application of the deep learning paradigm the main component. Special attention will be paid to privacy protection and data security in the context of biometrics. In addition, new large realistic annotated datasets for the related tasks are welcome.


 


Topics The topics of interest for this special issue include, but are not limited to, the following ones:


 


* Gait recognition with Deep Learning


* Face recognition (low resolution) at a distance with Deep Learning


* Person re-identification with Deep Learning


* Soft biometrics at a distance with Deep Learning


* Multimodal biometrics at a distance with Deep Learning


* Heterogeneous and cross-modal biometrics at a distance with Deep Learning


* Information fusion for biometrics with Deep Learning


* Incremental learning for biometrics at a distance with Deep Learning


* Semi- and weakly-supervised learning for biometrics at a distance with Deep Learning


* Algorithms for effective transfer learning applied to biometrics at a distance


* Multi-task learning applied to biometrics at a distance


* Processing and enhancement of low-quality biometric data


* Privacy protection and data security applied to Biometrics at a distance


 


Important Dates


* Paper submission due: 31/July/2022


* First review due: 30/September/2022


* Revised manuscript due: 30/November/2022


* Second review due: 15/January/2023


* Final manuscript due: 28/February/2023


 


Guest Editors


Manuel J. Marin-Jimenez (Lead GE), University of Cordoba, Spain. Email: mjmarin@uco.es


Shiqi Yu, SUSTech, China. Email: yusq@sustech.edu.cn


Yasushi Makihara, Osaka University, Japan. Email: makihara@am.sanken.osaka-u.ac.jp


Vishal Patel, Johns Hopkins University, USA. Email: vpatel36@jhu.edu


Maria de Marsico, Sapienza Università di Roma, Italy. Email: demarsico@di.uniroma1.it


Maneet Singh, AI Garage-Mastercard, India. Email: maneets@iiitd.ac.in


CFP, WINE 2022: The 18th Conference on Web and Internet Economics, Dec 12-16, Troy NY

============================================================
WINE 2022: The 18th Conference on Web and Internet Economics
Troy, NY, USA, December 12-16, 2022
https://www.cs.rpi.edu/wine2022/
============================================================
 
Over the past two decades, researchers in theoretical computer science, artificial intelligence, operations research, and economics have joined forces to understand the interplay of incentives and computation. These issues are of particular importance in the Web and the Internet that enable the interaction of large and diverse populations. The Conference on Web and Internet Economics (WINE) is an interdisciplinary forum for the exchange of ideas and results on incentives and computation arising from these various fields. WINE 2022 continues the successful tradition of the Conference on Web and Internet Economics (named Workshop on Internet & Network Economics until 2013), which was held annually from 2005 to present.
 
The program will feature invited talks, tutorials, paper presentations, a poster session, and a plenary session on spotlights beyond WINE. All paper submissions will be peer-reviewed and evaluated on the basis of the quality of their contribution, originality, soundness, and significance. Submissions are invited in, but not limited to, the following topics:
 
     – Algorithmic Game Theory
     – Algorithmic Mechanism Design
     – Market Design 
     – Auction Algorithms and Analysis
     – Computational Advertising
     – Computational Aspects of Equilibria
     – Computational Social Choice
     – Learning in Markets and Mechanism Design
     – Learning under Strategic Behavior
     – Coalitions, Coordination, and Collective Action
     – Economic Aspects of Security and Privacy
     – Economic Aspects of Distributed Computing and Cryptocurrencies
     – Econometrics, ML, and Data Science
     – Behavioral Economics and Behavioral Modeling
     – Fairness and Trust in Games and Markets
     – Price Differentiation and Price Dynamics
     – Revenue Management
     – Social Networks and Network Games
 
Authors of the accepted papers will have a choice to attend the conference virtually.
 
===============
Important Dates
===============
 
Paper submission deadline: July 7, 2022, 11:59pm Pacific Time
 
Author notification: before September 7, 2022
 
=================
Submission Server
=================
Easychair submission link:
https://easychair.org/conferences/?conf=wine2022
 
=================
Submission Format
=================
 
Authors are invited to submit extended abstracts presenting original research on any of the research fields related to WINE 2022.
 
An extended abstract submitted to WINE 2022 should start with the title of the paper, each author’s name, affiliation and e-mail address, followed by a one-paragraph summary of the results to be presented. This should then be followed by a technical exposition of the main ideas and techniques used to achieve these results, including motivation and a clear comparison with related work.
 
The extended abstract should not exceed 18 single-spaced pages (including references) using reasonable margins (at least one-inch margins all around) and at least 11-point font. If the authors believe that more details are essential to substantiate the claims of the paper, they may include a clearly marked appendix (with no space limit) that will be read at the discretion of the Program Committee. It is strongly recommended that submissions adhere to the specified format and length.
Submissions that are clearly too long may be rejected immediately. The above specifications are meant to provide more freedom to the authors at the time of submission. Note that accepted papers will be allocated 18 pages (including references) in the LNCS format in the proceedings (see below).
 
The proceedings of the conference will be published by Springer-Verlag in the ARCoSS/LNCS series, and will be available for distribution at the conference. Accepted papers will be allocated 18 pages total in the LNCS format in the proceedings. Submissions are encouraged, though not required, to follow the LNCS format (Latex, Word). More information about the LNCS format can be found on the author instructions page of Springer-Verlag (https://www.springer.com/cn/computer-science/lncs/conference-proceedings-guidelines).
 
Questions regarding the submissions can be directed to the PC chairs via wine2022chairs@gmail.com.
 
===========================
Conflict of Interest Policy
===========================
 
A conflict of interest (COI) is limited to the following categories:
1.            Family member or close friend.
2.            Ph.D. advisor or advisee (no time limit), or postdoctoral or undergraduate mentor or mentee within the past five years.
3.            Person with the same affiliation (department, not institute).
4.            Involved in an alleged incident of harassment (it is not required that the incident be reported).
5.            Reviewer owes author a favor (e.g., recently requested a reference letter).
6.            Frequent or recent collaborator whom you believe cannot objectively review your work.
 
Declaring COIs prevents the specified person from reviewing a paper, thereby constraining the matching process and so potentially negatively impacting review quality. For this reason, COIs should not be declared automatically based on a prior relationship (e.g., coauthor, friend, colleague in a different department at the same institution, etc.). Authors can contact the PC chairs directly if they have a conflict with an individual who is likely to be asked to serve as a subreviewer for the paper.
 
Even though EasyChair asks the authors to specify the type of conflict of interest when they declare one, the authors do *not* need to answer that question.  They may avoid answering it by choosing the option “Others”.
 
================
Best Paper Award
================
 
The program committee will decide upon a best paper award and a best student paper award.
 
================
Important Notice
================
 
To accommodate the publishing traditions of different fields, authors of accepted papers can ask that only a one-page abstract of the paper appear in the proceedings, along with a URL pointing to the full paper.
The authors should guarantee the link to be reliable for at least two years. This option is available to accommodate subsequent publication in journals that would not consider results that have been published in preliminary form in conference proceedings. Such papers must be submitted and formatted just like papers submitted for full-text publication.
 
Simultaneous submission of results to another conference with published proceedings is not allowed. Results previously published or presented at another archival conference prior to WINE 2022, or published (or accepted for publication) at a journal prior to the submission deadline of WINE 2022, will not be considered. Simultaneous submission of results to a journal is allowed only if the authors intend to publish the paper as a one-page abstract in WINE 2022. Papers that are accepted and appear as a one-page abstract can be subsequently submitted for publication in a journal but may not be submitted to any other conference that has a published proceeding.
 
==================
Forward to Journal
==================
 

A forward to journal program is initiated at WINE 2022. Please see the conference homepage for further and updated information.

1st CALL FOR PAPERS: IEEE approved International Conference “Advancements in Smart, Secure and Intelligent Computing (ASSIC-2022)

 

IEEE approved International Conference on Advancements in Smart, Secure and Intelligent Computing 

(ASSIC-2022)

19th- 20th November 2022 

(In Hybrid Mode)

https://www.assic.info/

Technically Co-Sponsored by IEEE Computer Society 

& 

IEEE Computer Society Bio-Inspired Computing Special Technical Community

 

Hosted by

 Kalinga Institute of Industrial Technology

Deemed to be University, Odisha, India 

https://kiit.ac.in/

                                                   

                                        

Dear Professor/Researcher,

Greetings!

 

ASSIC-2022 is an annual international conference technically co-sponsored by the IEEE Computer Society and IEEE Computer Society Bio-Inspired Computing Special Technical Community that facilitates a platform which not only presents smart computing paradigms but also incorporates machine intelligence based hi-tech system models with advanced security measures. The conference will be held at Kalinga Institute of Industrial Technology (KIIT), Deemed to be a University, Bhubaneswar from 19th to 20th  November 2022.

Prospective authors are invited to submit full research papers describing original and unpublished work (not currently under review by another conference/ journal) up to 7 pages in IEEE double-column format available at  https://www.ieee.org/content/dam/ieee-org/ieee/web/org/conferences/conference-template-a4.docx including figure, results, and references. All accepted & presented papers of the conference by duly registered authors, will be submitted to IEEE Xplore Digital Library (SCOPUS Indexed) for possible publication.

VenueKIIT Deemed to be University, Odisha, India,  (In Hybrid Mode)

Click here for paper submission: https://easychair.org/conferences/?conf=assic2022

 

Full Paper Submission- June 30, 2022

Notification of Acceptance- August 30, 2022

Camera Ready Paper Submission- September 30, 2022

Date of Conference- November 19 & 20, 2022

  

Topics of Interest include, but are not limited to:

 

TRACK I: AI-Enabled Computing

TRACK II: AI-Enabled Smart Healthcare

TRACK III: Intelligent Data Analysis and Secure Computing

 

For more details about the tracks kindly may visit our Conference Webpage: https://www.assic.info/

 

We look forward to a positive response from your end, confirming participation in the Conference. Kindly convey the details to your colleagues and encourage them to participate in the Conference.

 

Thank you in advance.

 

With sincere regards.

 

Organizing Committee, 

ASSIC 2022

 

 

Call For Papers BNAIC/BeNeLearn 2022

BNAIC/BeNeLearn is the reference AI & ML conference for Belgium, Netherlands & Luxembourg. The combined conference will take place from November 7th till November 9th in Mechelen, Belgium and is organized by the University of Antwerp, under the auspices of the Benelux Association for Artificial Intelligence (BNVKI).

More information about the conference may be found at: https://bnaic2022.uantwerpen.be/

SUBMISSION INFORMATION
Researchers are invited to submit unpublished original research on all aspects of Artificial Intelligence and Machine Learning. Additionally, high-quality research results already published in international AI/ML conference proceedings or journals are also welcome as extended abstracts.

Four types of submissions are invited:
* Type A: Regular papers
Papers presenting original work that advances Artificial Intelligence and Machine Learning. Position and review papers are also welcome. These contributions should address a well-developed body of research, an important new area, or a promising new topic, and provide a big picture view. Type A papers can be long (12 to 16 pages, including references and appendices) or short (<= 11 pages, including references and appendices). Contributions will be reviewed on the basis of their overall quality and relevance.
* Type B: Encore abstracts
Abstracts of already published work that has been published or accepted on or after June 1, 2021 to any AI/ML conference or journal. Authors are invited to submit the author version of their officially published paper together with an abstract of at most 2 pages (excluding references). Authors are encouraged to include further results obtained after the publication in their abstract and presentation. Submissions will be judged based on their originality and relevance to the conference. Authors may submit at most one type B paper of which they are the corresponding author.
* Type C: Demonstration abstracts
Proposals for demos should be submitted as a 2-page (excluding references) abstract. Demonstrations should also submit a short video illustrating the working of the system (not exceeding 15 minutes). Any system requirements should be mentioned in the submission. Demonstrations will be evaluated based on their originality and innovative character, the technology deployed, the purpose of the systems in interaction with users and/or other systems, and their economic and/or societal potential.
* Type D: Thesis abstracts
Bachelor and Master students are invited to submit a 2-page abstract (excluding references) of their completed AI/ML-related thesis. Supervisors should be listed. The thesis should have been accepted after June 1, 2021. Submissions will be judged based on their originality and relevance to the conference.
Reviews will be done single-blind. All submissions should include author names and their affiliations.

PRESENTATION
Type A, B, and D papers can be accepted for either oral or poster presentation.

PRIZES
Just like past years, there will be prizes for the best paper (type A), best demonstration (type C), and best thesis (type D).

PRE- & POST-PROCEEDINGS
Accepted contributions in all four categories will be included in the online (non-archival) conference proceedings. All contributions should be written in English, using the Springer CCIS/LNCS format (see https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines) and submitted electronically via EasyChair: https://easychair.org/conferences/?conf=bnaicbenelearn2022

Submission implies willingness of at least one author to register for BNAIC/BENELEARN 2022 and present the paper in person at the conference. For each paper, a separate author registration is required.

Similar to previous years we plan to organize a post-proceedings in the Springer CCIS series. A selection of type A long papers will be invited to submit to the post-proceedings (https://www.springer.com/series/7899).

IMPORTANT DATES
All deadlines are at 23:59, Anywhere on Earth time zone; please note that, in contrast with previous editions, the deadlines will not be extended.
– Submission registration deadline: August 26, 2022 For all submission types, it is required to submit a title and an abstract of a few lines by Aug 26, 2022, for purposes of paper bidding and assignment to the reviewers.
– Full submission deadline: September 2, 2022 – Author notification: October 3, 2022 – Camera ready submission deadline: October 17, 2022 – Conference: November 7-9, 2022 For any questions please contact us at bnaicbenelearn2022(at)easychair.org.

TOPICS OF INTEREST
We invite contributions on any topic in the broad area of Artificial Intelligence and Machine Learning. A non-exhaustive list of topics includes:
 – Automated Machine Learning and Meta-learning
 – Bayesian Learning
 – Case-based Learning
 – Causal Learning
 – Clustering
 – Computational Creativity
 – Computational Learning Theory
 – Computational Models of Human Learning
 – Data Mining & Knowledge Discovery
 – Data Visualisation
 – Deep Learning
 – Dimensionality Reduction
 – Ensemble Methods
 – Evaluation Frameworks
 – Evolutionary Computation
 – Graph Mining & Social Network Analysis
 – Inductive Logic Programming
 – Interactive AI / Human-in-the-loop Methods and Systems
 – Kernel Methods
 – Learning and Ubiquitous Computing
 – Learning in Multi-Agent Systems
 – Learning from Big Data
 – Learning from User Interactions
 – Learning for Language and Speech
 – Media Mining and Text Analytics
 – ML and Information Theory
 – ML Applications in Industry
 – ML for Data Science
 – ML for Scientific Discovery
 – ML in Non-stationary Environments
 – Natural Language Processing / Natural Language Understanding
 – Neural Networks
 – Online Learning
 – Pattern Mining
 – Predictive Modeling
 – Ranking / Preference Learning / Information Retrieval
 – Reinforcement Learning
 – Representation Learning
 – Robot Learning
 – Social Networks
 – Statistical Learning
 – Structured Output Learning
 – Time series modeling & prediction
 – Transfer and Adversarial Learning

Design by 2b Consult