This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Why signal processing? Signal processing is all around us. Broadly defined as the manipulation of signals — or mechanisms of transmitting information from one place to another — the field of signal processing exploits embedded information to […]
Accelerated Signal Processing with cuSignal Read More +
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. As machine learning (ML) has grown, many open source frameworks have come along, effectively democratizing what was once reserved for artificial intelligence (AI) researchers. Of these frameworks, TensorFlow has become the most popular for building and running
From Training to Inference: A Closer Look at TensorFlow for Developers Read More +
On March 24, 2021 at 9 am PT (noon ET), the Edge AI and Vision Alliance’s Founder, Jeff Bier, will present the free hour webinar “Deep Learning for Embedded Computer Vision: An Introduction,” in partnership with Vision Systems Design. Here’s the description, from the event registration page: Deep learning for embedded computer vision has made
Free Webinar Introduces Deep Learning for Embedded Computer Vision Read More +
What’s New: EXOS, a leader in the field of advancing human performance, is piloting Intel’s 3D Athlete Tracking (3DAT) technology in training aspiring professional athletes to reach their peak performance. As pro days loom, these athletes seek to take their game to the next level with 3DAT by leveraging artificial intelligence (AI) to gain actionable insights
Intel, EXOS Pilot 3D Athlete Tracking with Pro Football Hopefuls Read More +
The Embedded Vision Summit was held online on September 15-25, 2020, as an educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The presentations delivered at the Summit are listed below. All of the slides from these presentations are included in PDF form. To… September 2020 Embedded Vision Summit
September 2020 Embedded Vision Summit Slides Read More +
Smart City connected by IoT (Image by Tumisu from Pixabay) This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Whether you’re new to computer vision or an expert, you’ve probably heard about AlexNet winning the ImageNet challenge in 2012. That was the turning point in computer
Model Compression: Needs and Importance Read More +
Toly Kotlarsky, Distinguished Member of the Technical Staff in R&D at Zebra Technologies, presents the “Practical Guide to Implementing Deep Neural Network Inferencing at the Edge” tutorial at the September 2020 Embedded Vision Summit. In this presentation, Kotlarsky explores practical aspects of implementing a pre-trained deep neural network (DNN) inference on typical edge processors. First,
Jeff Bier, Founder of the Edge AI and Vision Alliance, interviews Monique Jones, Senior Software Engineer Team Lead at Intel, about her company’s DevCloud for the Edge developer toolset. Bier and Jones compare and contrast a DevCloud-based development flow versus the traditional approach that leverages a development board located at the engineer’s desk and directly
“DevCloud for the Edge,” an Alliance Conversation with Intel Read More +
This blog post was originally published at Deeplite’s website. It is reprinted here with the permission of Deeplite. Welcome back to the DNN model optimization series! Our recent paper on Deeplite’s unique optimization software, Neutrino™, won the “Best Deployed System” award at Innovative Applications of Artificial Intelligence 2021. For this occasion, we decided to dedicate this
Roland Memisevic, CEO, Chief Scientist and Founder of Twenty BN, presents the “Computer Vision-Based Personal Trainer That Runs On Your Phone” tutorial at the September 2020 Embedded Vision Summit. In this presentation, Memisevic describes Twenty BN’s journey towards building an AI-powered personal trainer that runs on your phone. The trainer takes the form of an
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