Kai Yu, Founder and CEO of Horizon Robotics, presents the “Journey and Sunrise Processors: Leading-Edge Performance for Embedded AI” tutorial at the May 2018 Embedded Vision Summit. As the nature of computation changes from logic to artificial intelligence, there’s a revolution happening at the edge. A new type of processor is required for this post-Moore’s-law […]
2-megapixel and 1.48-megapixel Sensors Cost-Effectively Enable Consumer and Industrial Computer Vision Applications With Precise Color and Near-Infrared Imaging, and Low Power Consumption SANTA CLARA, Calif. – Sept. 24, 2018 – OmniVision Technologies, Inc., a leading developer of advanced digital imaging solutions, today announced two new high-resolution additions to its family of global shutter image sensors—the
This market research report was originally published at Tractica's website. It is reprinted here with the permission of Tractica. Artificial intelligence (AI) processing today is mostly done in a cloud-based data center. The majority of AI processing is dominated by training of deep learning models, which requires heavy compute capacity. In the last 6 years,
Vikas Chandra, Senior Principal Engineer and Director of Machine Learning at Arm, presents the “Deep Learning on Arm Cortex-M Microcontrollers” tutorial at the May 2018 Embedded Vision Summit. Deep learning algorithms are gaining popularity in IoT edge devices due to their human-level accuracy in many tasks, such as image classification and speech recognition. As a
“Deep Learning on Arm Cortex-M Microcontrollers,” a Presentation from Arm Read More +
Paul Duckworth, Director of Engineering at Twisthink, presents the “Reduce Risk in Computer Vision Design: Focus on the User” tutorial at the May 2018 Embedded Vision Summit. Companies across a wide range of industries are considering ways to apply computer vision to innovate their products and services. With the vast potential of this exciting technology,
09/20/2018 – Baumer is enhancing the LX series with 2, 4 and 25 megapixel cameras with integrated JPEG image compression and frame rates of up to 140 fps. With the GigE cameras, you can save all down the line: from bandwidth through CPU load to storage space – this simplifies the system design and reduces
Megha Daga, Senior Technical Marketing Manager at Cadence, presents the “Neural Network Compiler: Enabling Rapid Deployment of DNNs on Low-Cost, Low-Power Processors” tutorial at the May 2018 Embedded Vision Summit. The use of deep neural networks (DNNs) has accelerated in recent years, with DNNs making their way into diverse commercial products. But DNNs consume vast
DNA 100 processor easily scales from 0.5 to 100s of TMACs for neural network inferencing in automotive, surveillance, robotics, drones, AR/VR, smartphone, smart home and IoT products SAN JOSE, Calif., September 19, 2018—Cadence Design Systems, Inc. (NASDAQ: CDNS) today announced the Cadence® Tensilica® DNA 100 Processor IP, the first deep neural-network accelerator (DNA) AI processor
Bernhard Friebe, Senior Director of Marketing for the Programmable Solutions Group at Intel, presents the “Enabling Software Developers to Harness FPGA Compute Accelerators” tutorial at the May 2018 Embedded Vision Summit. FPGAs play a critical part in heterogeneous compute platforms as flexible, reprogrammable, multi-function accelerators. They enable custom-hardware performance with the programmability of software. The
Artificial Intelligence Approach Learns Customer Image Quality Preferences to Accelerate Camera Tuning AutoSens Conference, Brussels, Belgium – September 18, 2018 – Algolux, the leading provider of machine learning optimization platforms for autonomous vision, today announced NaturalIQ©, an artificial intelligence (AI) approach that allows customers to automate the difficult task of subjective camera tuning by learning
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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