London Imaging Meeting

March 16th, 2021 Daniela Lopez de Luise

London Imaging Meeting 2021 (LIM 2021)
20-21 September
(Plus an additional day for short courses, TBA)
https://bit.ly/LIM_2021

The London Imaging Meeting (LIM 2021) promotes synergies between imaging science and deep learning.

We are interested in two aspects of deep-learning and imaging science research, case studies, or work-in-progress that lead and seed future research directions:
*Imaging science to improve deep learning performance
*Deep learning methods intended to improve imaging systems performance

PROGRAM TOPICS include but are not limited to
. The impact of imaging system design and optimization on DNN performance

. Imaging system modeling for data augmentation for DNN training

. Metrification of imaging performance for DNN input

. DNNs for metrification of imaging systems; optimization of imaging performance; and image quality prediction

. DNN components and domain adaptations for imaging systems

SUBMISSION DEADLINES
*Journal-first Deadline: 5 April
*Conference Proceedings Deadline: 30 April

CALL FOR PAPERS http://bit.ly/LIM_2021_CallforPapers

KEYWORDS: imaging science, imaging systems, imaging performance, deep learning, DNN, deep neural networks, AI, artificial intelligence

Connect with us on LinkedIn and @ImagingOrg #LondonImaging

Roberta Morehouse, CMP
Communications and Marketing Manager
Society for Imaging Science and Technology (IS&T)
-imaging across applications-imaging.org
IS&T is a non-profit organization dedicated to advancing science and technology in the field of imaging. 

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London Imaging Meeting

March 16th, 2021 Daniela Lopez de Luise
London Imaging Meeting 2021 (LIM 2021)
20-21 September
(Plus an additional day for short courses, TBA)
https://bit.ly/LIM_2021

The London Imaging Meeting (LIM 2021) promotes synergies between imaging science and deep learning.

We are interested in two aspects of deep-learning and imaging science research, case studies, or work-in-progress that lead and seed future research directions:
*Imaging science to improve deep learning performance
*Deep learning methods intended to improve imaging systems performance

PROGRAM TOPICS include but are not limited to
. The impact of imaging system design and optimization on DNN performance

. Imaging system modeling for data augmentation for DNN training

. Metrification of imaging performance for DNN input

. DNNs for metrification of imaging systems; optimization of imaging performance; and image quality prediction

. DNN components and domain adaptations for imaging systems

SUBMISSION DEADLINES
*Journal-first Deadline: 5 April
*Conference Proceedings Deadline: 30 April

CALL FOR PAPERS http://bit.ly/LIM_2021_CallforPapers

KEYWORDS: imaging science, imaging systems, imaging performance, deep learning, DNN, deep neural networks, AI, artificial intelligence

Connect with us on LinkedIn and @ImagingOrg #LondonImaging

Roberta Morehouse, CMP
Communications and Marketing Manager
Society for Imaging Science and Technology (IS&T)
-imaging across applications-imaging.org
IS&T is a non-profit organization dedicated to advancing science and technology in the field of imaging. 

Read More »

SI “Advanced Computer Vision Techniques for Autonomous Driving”

March 16th, 2021 Daniela Lopez de Luise
Dear Colleagues,

Autonomous driving (AD) refers to self-driving vehicles or any transport system moves without humans. Automotive systems are equipped with cameras and sensors to cover all the fields of view and range. Further, sensor architecture in AD includes multiple sets of cameras, radars, and LIDARs, as well as GPS-GNSS for absolute localization and inertial measurement units that provide a 3D pose of the vehicle in space. Representation of the environment state or scene understanding is utilized by a decision-making system to produce the final driving policy, which can be achieved by a combination of several perception or computer vision tasks such as semantic segmentation, motion estimation, depth estimation, and soiling detection. Computer vision is as a key technique in AD technologies. Thus, there is a need to explore new and emerging trends in computer vision for autonomous driving. This Special Issue aims to address the most up-to-date impacts of computer vision on progress autonomous driving research. Topics of interest include but are not limited to:

  • New trends on vision and sensors for autonomous driving;
  • Vision‐based traffic flow analysis and smart vehicle technologies;
  • Vehicle trajectory prediction in autonomous driving;
  • Vehicle classification and semantic segmentation;
  • Traffic sign detection, recognition, and scene understanding;
  • Detection, tracking, learning, and predicting on-road pedestrian behavior;
  • Object detection and tracking on Fisheye cameras for autonomous driving;
  • Unsupervised, weakly-supervised, and reinforcement deep.
Guest Editors

Prof. Dr. M. Hassaballah
Prof. Dr. Zhengming Ding
Dr. Senthil Yogamani

★☆★☆★☆★☆★☆★☆★☆☆★☆☆★☆☆★☆☆★☆☆★☆☆
M. Hassaballah, D.Eng., M.Sc., IEEE Member

Associate Professor of Computer Science

South Valley University, Qena, 83523, Egypt
Associate Editor: IET Image Processing


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Fwd: [CVML] [Journals] Call for Papers: Computers Journal – SI on Artificial Intelligence for Health — last weeks to submit (deadline: March 31)

March 16th, 2021 Daniela Lopez de Luise
***************************************************
MDPI COMPUTERS JOURNAL

Special Issue on Artificial Intelligence for Health

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Online Mechanics, Computers and Electrics Conference

March 14th, 2021 Daniela Lopez de Luise

INTERDISCIPLINARY CONFERENCE ON MECHANICS, COMPUTERS AND ELECTRICS

27-28 November 2021 (VIRTUAL)

www.icmece.org

 

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Dear authors,

( daniela_ldl@ieee.org )

Interdisciplinary Conference on Mechanics, Computers and Electrics (ICMECE 2021) will be held on 27-28 November 2021 as virtual. The goal of ICMECE-2021 is to gather scientists, engineers, researchers, technicians and industrial representatives to present the cutting-edge studies on Mechanical, Computer and Electrical Systems and form an interdisciplinary academic forum to discuss the scientific and engineering issues to arrive at more complete systems for the applications of future world.

The audience on the interdisciplinary issues can be M.Sc./Ph.D. students, post graduate Students, research Scholars, post-doc scientists and all other academicians related to Mechanical Engineering, Civil Engineering, Electrical, Electronics & Communication Engineering, Computer Science & Engineering, Communication Engineering, Mechatronics, and Natural Sciences. In addition, companies focusing on the entrepreneurship and research & development can participate, too. The conference will perform traditional research paper presentations as well as the keynote talks by prominent speakers focusing on the related state-of-the-art technologies in the interdisciplinary fields of the conference.

 

PUBLICATION

All accepted/presented papers will appear in ICMECE Conference Proceedings. Extended versions of the selected papers will be submitted to SCOPUS and SCI-indexed journals. Journal list will be improved till the conference time.

  • Journal of Energy Systems (Scopus)
  • Turkish Journal of Education (E-SCI)
  • Journal of Polytechnic (E-SCI)
  • International Journal of Automotive Science and Technology (TR Dizin)
  • Applied Solar Energy (Scopus)
  • Technology and Economics of Smart Grids and Sustainable Energy (Scopus)
     

KEYNOTE SPEAKERS

  • Prof. Dr. Peter R.N. Childs Imperial College London, UK
  • Prof. Dr. Josep M. Guerrero Aalborg University, Denmark
  • Prof. Dr. Adnan Sözen, Gazi University, Turkey
  • Prof. Dr. Francesco Cottone Perugia University, Italy
  • Prof. Dr. Nicu Bizon Pitesti University, Romania

 

Virtual Conference Days: 27-28 November 2021
Manuscript Submission Deadline: 1 September 2021

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