Journal special issue AI for CAV

March 2nd, 2021 Daniela Lopez de Luise

Special Issue “Artificial Intelligence for Connected and Automated Vehicles”

Applied Sciences (MDPI, ISSN 2076-3417, IF 2.47).

 

Deadline for manuscript submissions: 10 November 2021

 

https://www.mdpi.com/journal/applsci/special_issues/Applications_of_Artificial_Intelligence_for_Connected

 

Dear Colleagues,

Connected and automated vehicles (CAVs) will provide greater transport convenience and interconnectivity, increase mobility options, and reduce traffic accidents, congestion and emissions by exploiting Artificial Intelligence and communication technologies. At the same time, major barriers towards the public deployment of CAVs and the realization of smart cities exist, including the safety evaluation and validation of Artificial Intelligence-based vehicle functions. This Special Issue aims to bring together recent advances in methods and tools in the areas of machine learning, deep learning and computer vision, knowledge discovery, forecasting, as well as testing and validation to make connected and automated vehicles efficient and safe. We particularly invite contributions that identify and provide insight into the limitations of Artificial Intelligence-based techniques for connected and automated vehicles and/or advance the state of the art by breaking existing limitations.

 

Guest Editors

Prof.  Stratis Kanarachos

Prof. Aristotelis Naniopoulos

Dr. Dimitrios Nalmpantis

Prof. Vasile Palade

Dr. Islam Babaev

 

Keywords

Machine Learning

Deep Neural Networks

Computer Vision

Connected Vehicles

Automated Vehicles

CAV testing and validation

Big Data

Smart Cities

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Charla informativa del Programa de actualización en Derecho Informático

March 2nd, 2021 Daniela Lopez de Luise
Comunicación académica de la Facultad de Derecho de la Universidad de Buenos Aires
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Facultad de Derecho
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Unirse a la reunión
Más información: cursosadistancia@derecho.uba.ar
 

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Nuevo Webinar en vivo: Aprendizaje a distancia y laboratorios virtuales con MATLAB y Simulink

March 2nd, 2021 Daniela Lopez de Luise

Enseñanza a distancia
To view this email as a web page, click here.
MathWorks
  Seminario en vivo y en directo

  
Aprendizaje a distancia y laboratorios virtuales con MATLAB y Simulink
Fecha: marzo 16, 2021 laboratorios virtuales con MATLAB y Simulink
Hora: 3:00 pm New York
Centro América 1:00 pm
Ecuador – Perú: 2:00 pm
Chile: 4:00 pm UTC 4 

Regístrese
Acompáñenos y descubra nuevas herramientas basadas en la nube que ayudan a fomentar el aprendizaje independiente implementadas permitiendo que profesores y alumnos accedan a los contenidos de sus cursos en cualquier momento y desde cualquier lugar.

Algunos de los aspectos que discutiremos:

  • Cómo retar a sus alumnos utilizando problemas del mundo real con hardware, IoT, MATLAB Online y Simulink
  • Uso de cursos interactivos que los estudiantes puede completar a su propio ritmo
  • Creación de material didáctico interactivo con live scripts y apps de MATLAB
  • • Como evaluar y guiar el progreso de los estudiantes de manera automática con MATLAB Grader
  • Conectar a usuarios de MATLAB a través de la comunidad de aprendizaje a distancia

La asistencia es gratuita pero limitada.

Cordialmente,
Equipo de eventos de MathWorks
 
© 2021 The MathWorks, Inc.
MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See a list of additional trademarks.
Other product or brand names may be trademarks or registered trademarks of their respective holders.
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CallParticipation: ImageCLEF Social Media User Data Awareness Task

March 2nd, 2021 Daniela Lopez de Luise

ImageCLEFaware
https://www.imageclef.org/2021/aware

*** CALL FOR PARTICIPATION ***
Images constitute a large part of the content shared on social networks. Their disclosure is often related to a particular context and users are often unaware of the fact that, depending on their privacy status, images can be accessible to third parties and be used for purposes which were initially unforeseen. For instance, it is common practice for employers to search information about their future employees, online.

Most existing approaches which propose feedback about shared data focus on inferring user characteristics, and their practical utility is rather limited. We hypothesize that user feedback would be more efficient if conveyed through the real-life effects of data sharing.

The objective of the task is to automatically score user photographic profiles in a series of situations with strong impact on her/his life.

*** TASK ***
Given a set of social media user profiles, participants will propose machine learning techniques which provide a ranking of these in various (unaware) usage situations.

*** DATA SET ***
A data set of 500 user profiles with 100 photos per profile was created and annotated with an appeal score for a series of real-life situations via crowdsourcing. User profiles are created by repurposing a subset of the YFCC100M dataset. In accordance with GDPR, data minimization is applied, and participants receive only the information necessary to carry out the task in an anonymized form. Resources
include: (i) anonymized visual concept ratings for each situation modeled; (ii) automatically extracted predictions for the images that compose the profiles.

*** METRICS ***
The correlation with the ground truth will be measured using Pearson's correlation coefficient. The final score of each participating team will be obtained by averaging correlations obtained for individual situations.

*** IMPORTANT DATES ***
– Task registration opens: November 16, 2020
– Development data release: February 15, 2021
– Test data release: March 15, 2021
– Run submission: May 10, 2021
– Working notes submission: May 28, 2021
– CLEF 2021 conference: September 21-24, Bucharest, Romania

*** REGISTER ***
https://www.imageclef.org/2021#registration

*** OVERALL COORDINATION ***
Adrian Popescu, CEA LIST, France
Jérôme Deshayes-Chossart, CEA LIST, France Bogdan Ionescu, University Politehnica of Bucharest, Romania

On behalf of the Organizers,
Bogdan Ionescu
https://www.AIMultimediaLab.ro/

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Conferences: CASA 2021 Call for Papers (deadline extended to March 6)

March 2nd, 2021 Daniela Lopez de Luise


CASA 2021 Call for Papers

Technical Paper extended Deadline -March 6,  2021

 

The 34th International Conference on Computer Animation and Social Agents (CASA 2021) will be held virtually (online) July 15-17, 2021, from Ottawa, Canada. The conference is organized (tentatively in cooperation with ACM SIGGRAPH), supported by the Computer Graphics Society (CGS). 

We invite full papers on topics, including but not limited to Computer Animation, Embodied Agents, Social Agents, Virtual and Augmented Reality, and Visualization (see below for a detailed list).

Papers should be submitted by the 6th of March (27th of February) 2021. The best papers will be published in the special issue of Wiley’s Computer Animation and Virtual Worlds (CAVW). The remaining accepted papers will be published in conference proceedings (tentatively by Springer). 

All submissions will be reviewed via a double-blind review process. Authors must register for the conference for publications to be accepted.

 

IMPORTANT DATES (11:59 pm anywhere on Earth (AOE))

  • Submission deadline: Feb. 27, 2021 March 6, 2021
  • Notification of acceptance: Apr. 2, 2021 Apr. 6, 2021
  • Revised Camera ready: Apr. 30, 2021
  • Conference: Jul. 15-17, 2021

SCOPE AND LIST OF TOPICS

CASA invites submissions on a broad range of topics, including but not limited to:

Computer Animation

  • Motion Control
  • Motion Capture & Retargeting
  • Path Planning
  • Physics-based Animation
  • Procedural Modeling and Animation
  • Vision-based Techniques
  • Behavioral Animation
  • Artificial Life
  • Deformation
  • Crowd Simulation
  • Facial Modeling and Animation
  • Image-based Modeling and Animation
  • Multi-Scale Models
  • Knowledge-based Animation
  • Machine Learning for Animation
  • AI-based Modeling and Animation
  • Animation Compression and Transmission
  • Anthropometric Virtual Human Models
  • Acquisition and Reconstruction from Big Data
  • 3D Physiological Humans
  • Game-Based Learning
  • Medical Imaging 

Social Agents

  • Social Agents and Avatars
  • Emotion and Personality
  • Virtual Humans
  • Autonomous Actors
  • Social Robots
  • Intelligent Agents
  • Social and Conversational Agents
  • Inter-Agent Communication
  • Social Behavior
  • Crowd Behavior
  • Machine learning

Virtual and Augmented Reality

  • Artificial Agents in Virtual Reality
  • Mixed and Augmented Reality
  • Population Generation for Virtual Worlds
  • Virtual Cities
  • Virtual humans and avatars
  • Digital clones
  • VR health applications
  • Shared Virtual Environments
  • 3D Telepresence
  • Semantics and Ontologies for Animation and VR
  • Cultural Heritage Applications
  • Haptics

For more information, please visit the CASA 2021 website http://casa2021.ca/.

 

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