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call for participants 3DV2020 (virtual)

 3DV2020: THE INTERNATIONAL CONFERENCE ON 3D VISION
   November 25-28, 2020.
   Completely ONLINE Conference (originally in Fukuoka, Japan)
   http://3dv2020.dgcv.nii.ac.jp/index.html

KEYNOTE SPEAKERS
   Katsushi Ikeuchi (Microsoft/Univ. of Tokyo)
   Tomas Pajdla (Czech Technical Univ. in Prague)
   Yaser Sheikh (CMU/Facebook Reality Lab.)

Program details:
http://3dv2020.dgcv.nii.ac.jp/conferenceprogram.html

We look forward to your participation to 3DV2020!

CFP S+SSPR 2020 [Deadline extended 15 November 2020]

Please note that the submission deadline for S+SSPR 2020 has been extended to the *** 15th of November (firm deadline) ***.

Due to the ongoing covid-19 pandemic this edition of S+SSPR will be ONLINE and FREE. Accepted papers will be published in Springer’s Lecture Notes in Computer Science (LNCS) series.

The plain text CFP is listed below and for further information visit https://www.dais.unive.it/sspr2020/

Looking forward to your submissions,
S+SSPR organising committee

===

CALL FOR PAPERS
IAPR Joint International Workshops on
13th Statistical Techniques in Pattern Recognition (SPR)
18th Structural and Syntactic Pattern Recognition Workshop (SSPR)

Time and place: 19-22 January 2021, Online event
Paper submission deadline: 15 November 2020 (FIRM DEADLINE)

S+SSPR 2020 is a joint event organised by Technical Committee 1 (Statistical Pattern Recognition Technique) and Technical Committee 2 (Structural and Syntactical Pattern Recognition) of the International Association of Pattern Recognition (IAPR). Following the trend of previous editions, S+SSPR 2020 will be held in close proximity to the International Conference on Pattern Recognition (ICPR). Authors are invited to submit papers addressing topics in statistical, structural or syntactic pattern recognition and their applications. Accepted papers will be published in Springer’s Lecture Notes in Computer Science (LNCS) series.

For details see: http://www.dais.unive.it/sspr2020/

“Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment

Special Issue “Developing New Methods of Computational Intelligence and Data Mining in Smart Sensors Environment”

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section “Intelligent Sensors“.

Deadline for manuscript submissions: 21 April 2021.

https://www.mdpi.com/journal/sensors/special_issues/CI-DS

 

Special Issue Editor

Dr. Rafal Scherer
Guest Editor

Częstochowa University Of Technology, Czestochowa, Poland

Special Issue Information

Dear Colleagues,

Machine learning and computational intelligence methods, especially deep learning, can be used to create smart sensors that can perform testing, classification, or prediction. The whole menagerie of sensors, including inductive proximity sensors, photoelectric retro-reflective sensors, ultrasonic sensors, and others, can be beneficial to all areas—from Industry 4.0, through cars, to smart offices, homes, or hospitals. Synergistic hyperconnectivity brought by the emergence of the IoT will increase the applicability of such intelligent sensors. This Special Issue is addressed to all soft computing methods enabling in-sensor, edge, and similar computing for machine vision, data acquisition, or diagnostics. The methods covered will include deep learning, fuzzy logic, evolutionary methods, and various data mining techniques.

Dr. Rafal Scherer
Guest Editor

Keywords

  • sensor networks
  • smart/intelligent sensors
  • sensor devices
  • sensor technology and application
  • sensing principles
  • Internet of things
  • fuzzy logic
  • data mining
  • data fusion and deep learning in sensor systems

TCCLS 2020 PhD Thesis Award

 

 

Technical Committee on Computational Life Sciences (TCCLS) 2020 PhD thesis Award

https://tccls.computer.org/?page_id=670

 

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