2021 CVPR workshop on Fair, Data-efficient, and Trusted Computer Vision

March 24th, 2021 Daniela Lopez de Luise

Applied Sciences (IF *2.474*) Special Issue on “Deep Image Semantic Segmentation and Recognition”

March 23rd, 2021 Daniela Lopez de Luise

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Applied Sciences (ISSN 2076-3417, SCI impact factor: *2.474*) is currently running a Special Issue entitled 
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Deep Image Semantic Segmentation and Recognition.

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

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The deadline for submission is *end of May*.

If you work in this field, we would be honoured if you submit your work to the special issue. (Moreover, you can contact me and I will try to negotiate a better open access fee for you.)

Benefits of publishing with Applied Sciences:

1. Open access (unlimited and free access for readers).
2. Indexed by the Science Citation Index Expanded (Web of Science) [search for “Applied Sciences-Basel”], Scopus, Inspec (IET) and other databases.
3. Fast publication combined with thorough peer review (median processing time for peer-reviewed and a first decision in this journal in 2020 is about *15.9* days).
4. As indicated on journal's website, the APC of CHF 2000 in 2021 applies to accepted papers. (You may be entitled to a discount if you have previously received a discount code.)

For any questions regarding technical issues or the journal, please contact Mr. Steph Ke, the Assistant Editor of Applied Sciences at steph.ke@mdpi.com. 

We am looking forward to hearing from you.

Kind regards,        

in the name of the guest editors:
Prof. Dr. Aleš Jaklič,
Prof. Dr. Peter Peer,
Prof. Dr. Radim Burget,
Prof. Dr. Fran Bellas

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The 7th Int. Conf. on Machine Learning, Optimization & Data Science – LOD 2021

March 23rd, 2021 Daniela Lopez de Luise

 

October 5-8, Grasmere, Lake District, England – UK – Paper Submission Deadline: April 9

 

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Call for Papers: The 7th Int. Conf. on Machine Learning, Optimization & Data Science – LOD 2021, October 5-8, 2021 – Grasmere, Lake District, England – UK - Paper Submission Deadline: April 9

 

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Call for Papers: The 7th Int. Conf. on Machine Learning, Optimization & Data Science – LOD 2021, October 5-8, 2021 – Grasmere, Lake District, England – UK - Paper Submission Deadline: April 9

 

Dear Colleague, 

 

Apologies if you receive multiple copies of this announcement. 

Please kindly help forward it to potentially interested authors/attendees, thanks!

 

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Announcing the DodgeDrone Challenge & ICRA2021 Workshop on perception, planning, and control in highly dynamic environments

March 23rd, 2021 Daniela Lopez de Luise

General-purpose autonomy requires robots to interact with a constantly
dynamic and uncertain world.
We have organized an ICRA 2021 workshop on perception that brings
together amazing keynote speakers on this topic.
We encourage the submission of full research papers or extended
abstracts, please submit even if your work is only preliminary!

In conjunction with the workshop, we will hold the DodgeDrone Challenge,
where participants can build navigation algorithms for drones flying
through a forest! The winner of the competition will be awarded a
Skydio2 drone directly awarded from Skydio Autonomy!

Please visit the workshop website for further details:
https://uzh-rpg.github.io/PADE-ICRA2021/

==============
Important dates
==============

   *   Paper Submission deadline: 10.05.2021 AOE
   *   Notification date: 24.05.2021 AOE
   *   Challenge Submission deadline: 01.06.2021 AOE
   *   Workshop date: 04.06.2021 from 3pm to 8pm GMT (London time),
online.

=================
Overview and topics
=================

Humans and animals have an innate capacity to make predictions about
their surroundings, which allows them to react to both static and
dynamic obstacles during an action. Thanks to this ability, for example,
a seagull can catch a fast-moving fish in a short amount of time. In
contrast, artificial agents struggle to interact with complex and
dynamic environments and often rely either on the assumption that the
world is static or on simplified motion models of their surroundings.
This workshop will bring together researchers coming from different
backgrounds (computer vision, machine learning, and robotics) and
applications, to discuss existing solutions, research problems, and the
way forward to make robots interact with a permanently moving world.
Besides the usual mix of invited talks and poster presentations, we will
organize the DodgeDrones challenge, where participants will need to
develop perception and control algorithms to navigate a drone in a
highly dynamic environment.

   *   Perception: state estimation, object detection, free space
detection, etc.
   *   Simulation and modeling
   *   Transfer from simulation to reality
   *   Machine Learning for Robotics: end-to-end learning, learning from
demonstration, reinforcement learning
   *   Control, from high-level planning to high-fidelity tracking.
   *   Manipulation in unstructured environments.
   *   Application-specific challenges: interaction with humans,
navigation in the wild, AR/VR in dynamic scenes, etc.

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Submission
==========

All submitted papers will be reviewed by at least two international
experts on the basis of technical quality, relevance, significance, and
clarity. We accept extended abstracts (2-4 pages), experiences’ reports
(2-4 pages), or full research papers (up to 6 pages). We also encourage
the submission of live demos and working systems (up to 2 pages). All
accepted papers will appear on the workshop website. The paper version
should be a paper in pdf standard IEEE format. Accepted paper will be
made available on the website, and authors will be invited to give a
presentation about their work. Submission website:
https://easychair.org/conferences/?conf=pade2021.

==========
Challenge
==========

The DodgeDrone challenge revisits the popular dodgeball game in the
context of autonomous drones. Specifically, participants will have to
code navigation policies to fly drones between waypoints while avoiding
dynamic obstacles. Drones are fast but fragile systems: as soon as
something hits them, they will crash! Since objects will move towards
the drone with different speeds and accelerations, smart algorithms are
required to avoid them!

The competition consists of two challenges: (i) navigation in a static
environment, and (ii) navigation in a dynamic environment. The
navigation policy can only rely on on-board perception (dense depth,
agent, and goal location). These two modalities will help participants
to concentrate on different aspects of the navigation algorithm. Two
environments are used for the competition: a simple and irrealistic one
(which you should reserve for training and development); and a testing
one consisting of a photorealistic forest, where drones have to avoid
the vegetation, as well as the rocks and birds that will obstruct their
path.

A demo video can be found at the following link:
https://youtu.be/ZC1jfh2074o

=======================
Confirmed invited speakers
=======================

   *   Hayk Martiros, Skydio Autonomy
   *   Katherine J. Kuchenbecker, Max Planck Institute for Intelligent
Systems
   *   Alexsandra Faust, Google Brain
   *   Chelsea Finn and Annie Xie, Stanford
   *   Wolfram Burgard, University of Freiburg and Toyota Research
Institute
   *   Raquel Urtasun, University of Toronto
   *   Richard Newcombe, Facebook Reality Labs

=========
Organizers
=========

   *   Antonio Loquercio, University and ETH Zurich, Switzerland
   *   Davide Scaramuzza, University and ETH Zurich, Switzerland
   *   Luca Carlone, Massachusetts Institute of Technology (MIT), USA
   *   Markus Ryll, Technical University of Munich, Germany

On behalf of the organizers,
Antonio Loquercio

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Special Issue “Advances in Biomedical Image Processing and Analysis”

March 23rd, 2021 Daniela Lopez de Luise

Biomedical image analysis plays a vital role in diagnosing numerous pathologies, ranging from infectious diseases to cancer. Advanced methodologies for signal and/or image processing and analysis and biomedical analytics may be a powerful tool for classifying medical data, identifying individualized health trends, and finding evolutionary trajectories between normal and non-normal cases in many medical applications.

The rapid growth in algorithms and computing power in recent years has spurred the emergence of machine learning and image processing techniques as a new tool, which is rapidly entering every aspect of our lives, from intelligent personal assistance, such as Siri, Alexa, and Google Home, to self-driving cars. The medical community has begun taking advantage of these new possibilities to create new predictive models and improve existing models. For example, novel methods applying machine learning and image processing/analysis methods that are robust and theoretically sound to efficiently and intuitively solve learning tasks have become widespread across different facets of biomedical imaging for identifying complex patterns. Likewise, advances in biomedical imaging may lead to new technologies for developing predictive models for all diseases and guide the decision on who should receive preventive therapy.

To incorporate different aspects of health monitoring, authors are invited to submit papers reporting novel imaging methods with biomedical applications—in particular, exploration and research into the development of new algorithms for biomedical image processing and analysis – to this Special Issue. 

***************
Topics of interest include, but are not limited to, the following:

  • Computer-aided diagnosis;
  • Imaging biomarkers;
  • Image reconstruction;
  • Image registration;
  • Image segmentation;
  • Integration of imaging with non-imaging biomarkers;
  • Interpretability and explainability of machine learning;
  • Machine learning for biomedical applications;
  • Advances in machine learning methods;
  • COVID-19 and imaging;
  • Biomedical and biological image processing;
  • Deep learning for biomedical imaging;
  • Histopathological image analysis;
  • Mixed, augmented, and virtual reality;
  • Visualization in biomedical imaging.

Survey papers and reviews are also welcomed.

Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open-access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

This special issue is now open for submission.
Deadline for manuscript submissions: 30 October 2021.

Guest Editors
Dr. Michalis Vrigkas, University of Western Macedonia, Kastoria, Greece mvrigkas@uowm.gr
Dr. Christophoros Nikou, University of Ioannina, Ioannina, Greece, cnikou@uoi.gr
Dr. Ioannis A. Kakadiaris, University of Houston, Houston, TX, USA, ikakadia@central.uh.edu

____________________

Michalis Vrigkas, Ph.D.
Assistant Professor 
Department of Communication and Digital Media
University of Western Macedonia
GR 52100, Kastoria, Greece

Office: 313

Phone: +30 246 708 7298

E-mail: mvrigkas@uowm.gr | URL: mvrigkas.github.io

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