Smart Empower Innovation Labs Inc. introduces SmartExtract.AI, an innovative approach to IoT and BIG Data applications. SmartExtract.AI addresses limitations of cloud-only AI solutions by unlocking the secret ingredients of Machine learning.
For more information, visit www.smartempower.ca/smartextract
Smart Empower Innovation Labs Inc. to be part of the following technical panel session at the Global Petroleum Show Technical Conference, Calgary , 2019:
“Can The Energy Industry Play Catch up with IIoT ? What does it need to stay ahead of the curve“
We are excited to announce that Smart Empower Innovation Labs Inc. has been selected to receive support from Alberta Innovates to further advance our efforts towards AI-Enabled IoT Solutions.
A new research publication has been accepted on the application of our Sparse Learning Framework in IoT Big Data.
“A Multi-Scale Best Basis Sparse Learning Framework for Efficient IoT Big Data Applications“
We are delighted to announce that Smart Empower Innovation Labs Inc. has been selected to join IBM PartnerWorld through the IBM Global Entrepreneur program. We are excited for this news and the opportunities it opens. As a member of the IBM Innovation Ecosystem, Smart Empower Innovation Labs will receive support from IBM to accelerate our efforts to bring Artificial Intelligence to the Embedded computing paradigm for wide range of IoT applications.
A new publication has been submitted about our newly developed Sparse Learning Framework for Efficient IoT Big Data Applications.
A beta-release for our IoT learning framework is scheduled for release in Fall 2018. If interested in a demo run using your IoT data, contact us at email@example.com
With the escalating demand of IoT in industrial applications, Smart Empower Innovation Labs is working with our R&D collaborative partner,Great Wall of Information Security(GWiS) on adding decentralized Intelligence to traditional Internet of Things.
Two new research publications for Smart Empower Innovation Labs on role of Sparisty in Machine Learning:
1."Appearance-based Salient Features Extraction in Medical Images Using
Sparse Contourlet-based Representation", International Journal of Image,
Graphics and Signal Processing(IJIGSP), Sep. 2017
2."Multiscale Sparse Appearance Modeling And Simulation OF Pathological
Deformations",ICTACT Journal on Image and Video Processing ( Volume: 8 ,
Issue: 1 ), Sep 2017
We joined the Canadian Artificial Intelligence Association (CAIAC). CAIAC is concerned with the promotion of Artificial Intelligence through workshops, a national annual conference, and the Journal of Computational Intelligence.