Alexey Lopich, Principal Hardware Engineer and Team Lead at Arm, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Lopich demonstrates Arm’s Object Detection processor, showing how it detects objects – from 50×60 pixels to full screen – in real time, at high speed (60fps) and in high resolution (Full HD). He […]
Arm Demonstration of the Company’s Object Detection Processor Read More +
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
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Steve Steele, Director of Platforms in the Machine Learning Group at Arm, presents the “Project Trillium: A New Suite of Machine Learning IP from Arm” tutorial at the May 2018 Embedded Vision Summit. Machine learning processing engines today tend to focus on specific device classes or the needs of individual sectors. Arm’s Project Trillium changes
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Gian Marco Iodice, Senior Software Engineer in the Machine Learning Group at Arm, presents the “Even Faster CNNs: Exploring the New Class of Winograd Algorithms” tutorial at the May 2018 Embedded Vision Summit. Over the past decade, deep learning networks have revolutionized the task of classification and recognition in a broad area of applications. Deeper
Roberto Mijat, Director of Software Product Management in the Business Segment Group at ARM, presents the "Computer Vision on ARM: Faster Ways to Optimize Software for Advanced Mobile Computing Platforms" tutorial at the May 2017 Embedded Vision Summit. Mobile computing platforms are ubiquitous, and therefore provide an exciting vehicle for the deployment of new computer
Tim Ramsdale, General Manager of the Imaging and Vision Group at ARM, presents the "This Changes Everything — Why Computer Vision Will Be Everywhere" tutorial at the May 2017 Embedded Vision Summit. Computer vision, or teaching machines to see, will be revolutionary – it will change everything. Beyond the obvious markets where it is having
First processors based on ARM DynamIQ technology take a big step towards boosting AI performance by more than 50x over the next 3-5 years ARM Cortex-A75 delivers massive single-thread compute uplift for premium performance points ARM Cortex-A55 is the world’s most versatile high-efficiency processor ARM Mali-G72 GPU expands VR, gaming and Machine Learning capabilities on premium
Accelerating AI Experiences from Edge to Cloud Read More +
Tim Hartley, Senior Product Manager in the Imaging and Vision Group at ARM, presents the "Computer Vision on ARM: The Spirit Object Detection Accelerator" tutorial at the May 2017 Embedded Vision Summit. In 2016, ARM released Spirit, a dedicated object detection accelerator, bringing industry-leading levels of power- and area-efficiency to computer vision workflows. In this
Gian Marco Iodice, Software Engineer at ARM, presents the "Using SGEMM and FFTs to Accelerate Deep Learning" tutorial at the May 2016 Embedded Vision Summit. Matrix Multiplication and the Fast Fourier Transform are numerical foundation stones for a wide range of scientific algorithms. With the emergence of deep learning, they are becoming even more important,
“Using SGEMM and FFTs to Accelerate Deep Learning,” a Presentation from ARM Read More +
Tim Hartley, Product Manager in the Personal Mobile Compute Business Line at ARM, presents the "Lessons Learned from Bringing Mobile and Embedded Vision Products to Market" tutorial at the May 2016 Embedded Vision Summit. Great news: technology is finally at a point where we can build sophisticated computer vision applications that run on mass market
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