Orr Danon, CEO of Hailo, presents the “Emerging Processor Architectures for Deep Learning: Options and Trade-offs” tutorial at the May 2019 Embedded Vision Summit. In the past year, numerous new processor architectures for machine learning have emerged. Many of these focus on edge applications, reflecting the growing demand for deploying machine learning outside of data […]
Sandeep Hiremath, Product Manager, and Bill Chou, Senior Computer Vision Scientist, both of MathWorks, present the "Deploying Deep Learning Models on Embedded Processors for Autonomous Systems with MATLAB" tutorial at the May 2019 Embedded Vision Summit. In this presentation, Hiremath and Chou explain how to bring the power of deep neural networks to memory- and
Pulin Desai, Vision Product Marketing Director at Cadence, presents the "Highly Efficient, Scalable Vision and AI Processors IP for the Edge" tutorial at the May 2019 Embedded Vision Summit. This presentation describes the architecture of the latest Tensilica-based vision and AI processor family, and illustrates how easily vision algorithms (e.g., SLAM, 3D capture) and AI
Yury Gorbachev, Principal Engineer at Intel, presents the "How to Get the Best Deep Learning Performance with the OpenVINO Toolkit" tutorial at the May 2019 Embedded Vision Summit. Tremendous recent progress in deep learning and computer vision algorithms has made it possible to create innovative applications that were not previously feasible. However, moving from academic
Ronak Shah, Director of AI Marketing Strategy at Intel's Programmable Solutions Group, presents the "AI+: Combining AI and Other Critical Functions Using Intel FPGAs" tutorial at the May 2019 Embedded Vision Summit. AI is increasingly being deployed in vision applications, and most of these applications require other functionality in addition to AI. For example, a
John Williams, CTO and co-founder of Kudan, presents the "Commercial Grade SLAM Frameworks for Indoor and Outdoor Applications" tutorial at the May 2019 Embedded Vision Summit. SLAM (simultaneous localization and mapping) is an essential technology for any device that requires an understanding of its location and orientation in the physical world. Kudan is the only
Ian Billing, Quality Assurance Manager at Teknique, presents the "Accelerating Smart Camera Time to Market Using a System-on-module Approach" tutorial at the May 2019 Embedded Vision Summit. Bringing a vision system product to market can be costly and time-consuming. Teknique’s Oclea System-on-Module (SoM) is an off-the-shelf, integrated camera module that enables device makers to streamline
Sebastian Günther, Host Systems Competence Center Lead at Allied Vision Technologies, presents the "Accessing Advanced Image Processing Feature Sets with Alvium Cameras Using a V4L2/GenICam Hybrid Driver" tutorial at the May 2019 Embedded Vision Summit. Camera device drivers are a critical component for all embedded vision systems, providing an essential interface between the camera and
Petronel Bigioi, CTO for Imaging at Xperi, presents the "An Ultra-low-power Multi-core Engine for Inference on Encrypted DNNs" tutorial at the May 2019 Embedded Vision Summit. Neural network encryption is a useful method to secure a company’s IP. This presentation focuses on the design details of an ultra-low-power, scalable neural network core capable of performing
Pete Warden, Staff Research Engineer and TensorFlow Lite development lead at Google, presents the "Using TensorFlow Lite to Deploy Deep Learning on Cortex-M Microcontrollers" tutorial at the May 2019 Embedded Vision Summit. Is it possible to deploy deep learning models on low-cost, low-power microcontrollers? While it may be surprising, the answer is a definite “yes”!
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
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