Events
Arduinos, 3D printing, Lego Mindstorms and displays, submarine
robots, and AI, where can you find all this? All of this and MUCH MORE will be at the IEEE Ottawa Robotics
Competition (ORC), Ottawa’s largest robotics competition for grade 5 to 12
students. The ORC is taking place on Sunday,
June 2nd at Earl of March
Secondary School. Best times to show up are between 10:30 am to 12:30 pm and 1:30 pm to 4 pm. The ORC is completely
open to the public, so invite your friends and family too!
Check out previous competitions at https://youtube.com/user/ieeeorc/videos.
If you have any questions, please feel free to email us at orcinfo@ieeeottawa.ca.
![Distinguished Lecture by Professor Mohamed-Slim Alouini "Smart Villages: When Connectivity Meets Affordability" @ Carleton University, ME4463 | Ottawa | Ontario | Canada](https://www.ieeeottawa.ca/wp-content/uploads/2019/05/PELS-Day-300x209.jpg)
The role of Internet and Communication Technology (ICT) in
bringing about a revolution in almost all aspects of human life needs no
introduction. It is indeed a well-known fact that the transmission of
information at a rapid pace has transformed all spheres of human life such as
education, health, and economy to name a few. In addition, with the advent in
Electronics and Photonics Technology (EPT), we have observed sustained growth
and expansion in computation and display technology. From user demography
perspective, urbanized population are the major beneficiary of such advances.
Therefore, the benefits of ICT and EPT are yet to be experienced by almost 4
billion people in the world who are still “unconnected or under-connected†and
suffer as such from the “digital divide,†a term coined in order to emphasize
the lack of ICT infrastructure in many parts of the world.
Major challenges for widespread adoption of ICT and EPT in
these areas are related to cost, lack of power supply, and complexities
associated with learning and usage. However, if we can categorically overcome
these challenges, then these technologies can be used for food, water, shelter,
energy, environment, education, healthcare, and security. In addition, the
wide-spread availability of these technologies, will lead to smart suburbs,
smart towns, smart villages, etc., without the need to necessarily live in
smart cities. This would reverse the trend and allow a more sustainable world
with a more balanced distribution of the population density. In this context,
this talk will present recently proposed solutions to provide high speed
connectivity in rural areas along progress in affordable electronics to serve
and contribute to the development of far-flung regions.
In particular, new solutions for both: (i) integrated
satellite-airborne-ground networks providing global coverage and connectivity
and (ii) terrestrial mesh/multi-hop directive networks connecting underserved
areas will be discussed.
Moreover, some examples of democratized wearable
electronics using Do-It-Yourself (DIY) assembly of paper along Android DIY
applications capturing and displaying vital health signs over connected
smartphones for real-time diagnosis will be presented.
IEEE Ottawa Seminar Series on AI and Machine Learning
Hosted by IEEE Ottawa PHO Chapter, EMBS Chapter, CS Chapter, and SP Chapter Jointly with Vitesse Reskilling
Application of
Deep Learning for Medical Image Analysis
Fatemeh Zabihollahy
Carleton University
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Wednesday, June 26, 2019
359 Terry Fox Drive, Suite 200, Kanata, Ontario
11:30 – 13:30
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Medical imaging, (e.g., computed tomography (CT), magnetic resonance
imaging (MRI), positron emission tomography (PET), mammography, ultrasound,
X-ray) has advanced at a rapid speed over last decades. Currently, the medical
image interpretation is mostly performed by human experts, which is a tedious
task and subject to high inter-operator variability. Deep learning is providing
exciting solutions for medical image analysis problems. Recent advances in deep
learning have helped to identify, classify, and quantify patterns in medical
images. In this seminar, we introduce the principles and methods of deep
learning concepts, particularly convolutional neural network (CNN). We show how
CNN operates. I will describe several interesting applications of deep learning
for medical image analysis, including my recent works on segmenting myocardial
scar (injured) tissue in the heart, prostate tumor detection, and kidney lesion
localization in 3D MRI and CT images.
Biography
Fatemeh Zabihollahy is currently
a Ph.D. candidate at Carleton University. She obtained her MASc (2016) and BASc
(2001) both in Biomedical Engineering from Carleton University, Canada and
Shahid Beheshti University, Iran, respectively. She worked in the medical
devices industry as an R&D engineer for ten years. Her research interest is
in the field of application of deep learning techniques for medical image
analysis.
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Event
is free, but space is limited. All
participants must register in advance. Â
Please
follow the link to register
https://ieeeottawaaiml2019jun26.eventbrite.ca
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For more information, please contact: Kexing Liu kexing.liu@ieee.org