Special Session on “Beyond Traditional Sensing for Intelligent Transportation” – ITSC2020

February 18th, 2020 Daniela Lopez de Luise
ITSC 2020 – The 23rd IEEE International Conference on Intelligent Transportation Systems

September 20-23, 2020. Rhodes, Greece.

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Special Session on
*Beyond Traditional Sensing for Intelligent Transportation*
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https://tinyurl.com/u5bz6v9
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Over the past few decades, sensors have not only become more advanced but also made impressive strides across an increasing number of sensing modalities.
Despite the improved capabilities and breadth of available sensor systems, those used for intelligent transportation have remained relatively uniform across platforms; as a result, the algorithms and techniques being designed do not take full advantage of the rich information modern sensors can provide.
Since all tasks — including perception, localisation, decision-making, and learning — are built on top of sensing, exploring alternative approaches to sensing is a compelling research area that can render all subsequent tasks more robust and accurate.

The objective of this special session is to explore unconventional sensing for intelligent transportation in three ways.
Firstly, it will investigate sensor systems that are not typically applied to certain transportation tasks, such as radar for precise localisation, audio for failure detection, and RF sensing for road traffic estimation.
Secondly, it will explore untraditional sensor configurations and placements, such as ground-facing cameras using shadows to detect occluded moving objects.
Lastly, it will look into the sensing of commonly overlooked information, such as the use of atmospheric sensors for gauging road surface traction or in-vehicle sensors for driving analysis.
Via these three themes, this special session aims to stimulate discussion and research into untraditional sensing in order to improve the reliability and accuracy of transportation systems.

Topics of interest include, but are not limited to:
* Localisation and navigation using radars (e.g., scanning, Doppler, and ground-penetrating);
* Ego-noise and soundscape modelling and interpretation (e.g., sound-based failure detection, terrain/road surface status classification, urban sound source detection and localisation);
* Event-based (neuromorphic) vision for localisation and perception in challenging scenarios;
* Multi-spectral imaging (e.g. IR or polarimetric cameras for localisation and perception under difficult visibility);
* In-vehicle sensing and wearable computing for failure detection, driver and passenger behaviour modelling;
* Far infrared sensing;
* Texture odometry;
* Novel sensor hardware and designs;
* Unconventional sensor placements or multi-sensor systems;
* Optimal sensor scheduling and control in complex and/or multi-agent / social environments;
* Astronomical (skyward-facing), atmospheric or odor-based sensing;
* IoT technology for intelligent transportation and Internet of Vehicles (IoV);
* Passive Wireless/RF sensing.

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*Important Dates*
Paper Submission Deadline: March 02, 2020
Notification of Acceptance: May 10, 2020
Final Paper Submission Deadline: June 10, 2020
Conference Dates: September 20-23, 2020    

Authors are kindly invited to notify the organisers of their submissions.

Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of ITSC2020. Submissions to regular and special sessions follow identical format, instructions, deadlines and procedures.

Please find more info on the ITSC2020 website
https://www.ieee-itsc2020.org/

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*Organizers*
Letizia Marchegiani, Aalborg University, Denmark. lm@es.aau.dk
Dimitri Ognibene, University of Essex, UK. dimitri.ognibene@essex.ac.uk
Daniele De Martini, University of Oxford, UK. daniele@robots.ox.ac.uk
Xenofon Fafoutis, Technical University of Denmark (DTU), Denmark. xefa@dtu.dk
Yan Wu, A*STAR Institute for Infocomm Research, Singapore. wuy@i2r.a-star.edu.sg
Sahar Abbaspour, Volvo Car Corporation, Sweden. sahar.abbaspour@volvocars.com
Matthew Gadd, University of Oxford, UK. mattgadd@robots.ox.ac.uk

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DOCTORAL SYMPOSIUM CALL FOR SUBMISSIONS – Eye Tracking Research and Applications (ETRA 2020)

February 18th, 2020 Daniela Lopez de Luise

Eye Tracking Research and Applications (ETRA 2020) – DOCTORAL SYMPOSIUM CALL FOR SUBMISSIONS

 

The 2020 ACM Symposium on Eye Tracking Research and Applications will offer a Doctoral Symposium, where doctoral students get an opportunity to meet other students and experienced researchers to get feedback on their research in a friendly collegial environment. We invite abstracts from doctoral students who have a defined topic in the area of eye tracking research and applications, and whose work is still in a phase where it can be influenced by the feedback received at the symposium. Outstanding abstracts from students who have not yet been accepted into a doctoral program will also be considered. Participants will be selected based on an extended abstract (3 pages + 1 additional page for references) describing the thesis work, its current status, and future work. The abstract will be included in the ETRA adjunct conference proceedings and published at ACM.

 

Objective

The objective of the doctoral symposium is to provide feedback on the student’s work and facilitate the exchange of ideas between other researchers and students working on related topics. The main symposium also offers an excellent opportunity to network with researchers with similar interests.

 

Submissions

Participants will be selected based on an extended abstract (3 pages + 1 additional page for references) describing the thesis work, the impact of the work, its current status, and future work. The abstracts will go through a one-cycle review process. The goal of the review process is to ensure that students have a defined topic and are still early enough in their studies to benefit from the feedback and guidance received during the symposium. The abstract (3 pages + 1 additional page for references) should describe:

 

* Research Objectives

* Problem Statement and Hypotheses

* Approach and Methods

* Preliminary Results

* Broader Impact

* Plans for future work

 

The role of eye tracking should be clear from the abstract. Please note that the extended abstract should have an abstract section on the top just like any other ETRA submission.

 

Please use the appropriate template, available for both LaTeX and Word (Overleaf Project, Word Template, LaTex Template (v1.65)) on our call for submissions page at http://etra.acm.org/2020/doctoralsymposium.html. Additional information about submissions available at http://etra.acm.org/2020/submissionprocess.html.

 

In addition, the submission should include:

* A concise CV (max. 3 pages)

* A brief statement indicating how the student expects to benefit from involvement in the ETRA Doctoral Symposium (max. 1 page)

* A letter of recommendation from the student’s research advisor. The letter should indicate how long the student has been enrolled in the doctoral program and discuss the status of the student’s work (max. 1 page).

 

Abstracts and accompanying documents should be submitted via Precision Conference System to the Doctoral Symposium track at https://new.precisionconference.com/user/login?society=etra

 

Important Dates (Time Zone: AoE)

Doctoral Symposium Important Dates

March 13, 2020 Submission deadline

March 20, 2019 Decisions announced

April 2, 2020       Camera ready abstracts due

June 2, 2020        ETRA Doctoral Symposium

 

Accepted abstracts will be available in the ACM digital library as part of the ETRA 2020 adjunct proceedings.

 

Doctoral Symposium Co-Chairs

 

For more information please contact:

Bonita Sharif (bsharif@unl.edu), Computer Science and Engineering, University of Nebraska – Lincoln,  USA

Michael Dodd (mdodd2@unl.edu), Psychology, University of Nebraska – Lincoln,  USA

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[Courses] Machine Learning Seminar

February 18th, 2020 Daniela Lopez de Luise
Hello all,

We're hosting a 2-day Machine Learning seminar taught by Kevin Grimm on June 25-26, 2020 in Philadelphia.

This two-day seminar is a thorough introduction to machine learning techniques. Topics include cross-validation, multiple regression, basic variable selection methods, an overview of the R statistical framework, multivariate adaptive regression splines, lasso regression, classification and regression trees, bagging, and random forests.

Participants can expect to gain both the background and hands-on practice to master machine learning methods. Please pass this info along to colleagues, grad students, or anyone else who might be interested.

Click here for more information or to register. Please email info@statisticalhorizons.com with any questions.

Thanks,
Ashley


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CFP: Image and Vision Computing

February 18th, 2020 Daniela Lopez de Luise

Image and Vision Computing

CALL FOR PAPERS

Special Issue on Advances in Domain Adaptation for Computer Vision

 

Aim and Scope: 

In daily routines, humans, not only learn and apply knowledge for visual tasks but also have intrinsic abilities to transfer knowledge between related vision tasks. For example, if a new vision task is relevant to any previous learning, it is possible to transfer the learned knowledge for handling the new vision task. In developing new computer vision algorithms, it is desired to utilize these capabilities to make the algorithms adaptable. Generally, traditional computer vision methods do not adapt to a new task and have to learn the new task from the beginning. These methods do not consider that the two visual tasks may be related and the knowledge gained in one may be applied to learn the other one efficiently in lesser time. Domain adaptation for computer vision is the area of research, which attempts to mimic this human behavior by transferring the knowledge learned in one or more source domains and use it for learning the related visual processing task in the target domain. Recent advances in domain adaptation, particularly in cotraining, transfer learning, and online learning have benefited computer vision research significantly. For example, learning from high-resolution source domain images and transferring the knowledge to learning low-resolution target domain information. This special issue will focus on the recent advances in domain adaptation for different computer vision tasks. 


 Topics of interest include, but are not limited to: 

·       Domain adaptation for machine learning frameworks for learning deep representations 

·       Domain adaptation for face detection/recognition and tracking

·       Domain adaptation for object detection/ recognition and tracking

·       Domain adaptation and hybrid models for real-time computer vision tasks

·       Domain adaptation for human pose detection/recognition and estimation 

·       Domain adaptation for event/action detection and recognition

·       Domain adaptation for few-shot learning

·       Domain adaptation for deep neural network optimization


Important Dates: 

Paper submission due: May 31, 2020 

First notification: July 31, 2020 

Revision submission due: September 30, 2020 

Final decision: November 30, 2020 


Paper evaluation and submission: 

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, the significance of contribution, technical quality, and quality of presentation, by at least two independent reviewers (the papers will be reviewed following standard peer-review procedures of the Journal). Each paper will be reviewed rigorously and possibly in two rounds. Prospective authors should follow the formatting and Instructions of Image and Vision Computing at https://www.elsevier.com/journals/image-and-vision-computing/0262-8856/guide-for-authors, and invited to submit their papers directly via the online submission system at https://www.editorialmanager.com/IMAVIS/default.aspx. When submitting your manuscript please select the article type "VSI: Advances in Domain Adaptation for Computer Vision (ADACV)" Please submit your manuscript before the submission deadline. https://www.journals.elsevier.com/image-and-vision-computing/call-for-papers/advances-in-domain-adaptation-for-computer-vision 


Guest Editors:

Dr. Pourya Shamsolmoali 

Institute of Image Processing & Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China. 

Email: pshams@sjtu.edu.cn 


Prof. Salvador Garcaí 

Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain. 

Email: salvagl@decsai.ugr.es 


Dr. Huiyu Zhou 

Department of Informatics, University of Leicester, Leicester, UK. 

Email: hz143@leicester.ac.uk 


Prof. M. Emre Celebi 

Department of Computer Science, University of Central Arkansas, Conway, Arkansas, USA. 

Email: ecelebi@uca.edu 

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Well funded AMTD Waterloo Global Talent Postdoctoral Fellowship

February 18th, 2020 Daniela Lopez de Luise

Dear colleagues,

 

Please share widely.

 

The Multisensory Brain and Cognition Lab at the University of Waterloo, Canada is seeking postdoctoral applicants for a newly announced AMTD Waterloo Global Talent Postdoctoral Fellowship. The application deadline is March 16, 2020.

 

Information about and how to apply for this prestigious one or two year fellowship (funding includes a $75,000 annual salary, an engagement fund of $7,500 plus access to additional funds to create disruptive research dissemination opportunities) can be found here:

 

https://uwaterloo.ca/graduate-studies-postdoctoral-affairs/welcome-postdoctoral-affairs/find-postdoc-funding/amtd-waterloo-global-talent-postdoctoral-fellowship

 

The Multisensory Brain and Cognition Lab has graduated a number of successful postdoctoral fellows and provides an enriching research environment for fellows to develop their own research programs related to multisensory processing, self-motion perception and action, aging, augmented and virtual reality. The lab is equipped with a 6 degree-of-freedom MOOG motion simulator, a high frequency ProPixx projector, multiple head mounted displays, motion capture, force plates, biopotential recording, and employs an array of techniques including psychophysics, computational modeling, galvanic vestibular stimulation, transcranial Direct Current Stimulation, Electroencephalography, and Transcranial Magnetic Stimulation. 

 

The incumbent will benefit from a multidisciplinary training and research environment spanning academia and industry. The lab is housed in the Department of Kinesiology and the Centre for Community, Clinical and Applied Research Excellence (CCCARE), which is a unique facility that integrates research and community programs to develop new health interventions related to exercise for health and disease prevention, nutrition and health, brain training, vascular and metabolic health, injury prevention, and maximizing of mobility and prevention of falls. The lab is also associated with The Games Institute, which conducts research into the past, present, and future of games with representation from all facilities.

 

Applicants interested in applying for the AMTD Waterloo Global Talent Postdoctoral Fellowship under the supervision of Lab Director Michael Barnett-Cowan should contact him directly at mbc@uwaterloo.ca. Past published work can be found here: https://scholar.google.com/citations?user=WgcCbxoAAAAJ&hl=en.

 

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