Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the "Vision Acceleration API Landscape: Options and Trade-offs" tutorial at the May 2017 Embedded Vision Summit. The landscape of APIs for accelerating vision and neural network software using specialized processors continues to rapidly evolve. Many industry-standard APIs, such as OpenCL and OpenVX, […]
Although incorporating visual intelligence in your next product is an increasingly beneficial (not to mention practically feasible) decision, how to best implement this intelligence is less obvious. Image processing can optionally take place completely within the edge device, in a network-connected cloud server, or subdivided among these locations. And at the edge, centralized and distributed
Vinod Kathail, Distinguished Engineer and leader of the Embedded Vision team at Xilinx, presents the "Caffe to Zynq: State-of-the-Art Machine Learning Inference Performance in Less Than 5 Watts" tutorial at the May 2017 Embedded Vision Summit. Machine learning research is advancing daily with new network architectures, making it difficult to choose the best CNN algorithm
Jitendra Malik, Arthur J. Chick Professor and Chair of the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, presents the "Deep Visual Understanding from Deep Learning" tutorial at the May 2017 Embedded Vision Summit. Deep learning and neural networks coupled with high-performance computing have led to remarkable advances in computer
Michael Melle, Sales Development Manager at Allied Vision, and Felix Nikolaus, Firmware Designer at Allied Vision, presents the "A Multi-purpose Vision Processor for Embedded Systems" tutorial at the May 2017 Embedded Vision Summit. This presentation gives an overview of an innovative vision processor that delivers the superior image quality of industrial cameras while enabling the
Sammy Sidhu, Senior Engineer at DeepScale, presents the "A Shallow Dive into Training Deep Neural Networks" tutorial at the May 2017 Embedded Vision Summit. In this talk, Sidhu introduces the basics of training deep neural network models for vision tasks. He begins by explaining fundamental training concepts and terms, including loss functions and gradients. He
“A Shallow Dive into Training Deep Neural Networks,” a Presentation from DeepScale Read More +
Shehrzad Qureshi, Senior Engineer at BDTI, presents the "Demystifying Deep Neural Networks" tutorial at the May 2017 Embedded Vision Summit. What are deep neural networks, and how do they work? In this talk, Qureshi provides an introduction to deep convolutional neural networks (CNNs), which have recently demonstrated impressive success on a wide range of vision
“Demystifying Deep Neural Networks,” a Presentation from BDTI Read More +
Jeff Bier, Founder of the Embedded Vision Alliance and Co-founder and President of BDTI, presents the "1000X in Three Years: How Embedded Vision is Transitioning from Exotic to Everyday" tutorial at the May 2017 Embedded Vision Summit. Just a few years ago, it was inconceivable that everyday devices would incorporate visual intelligence. Now it’s clear
Michael Tusch presents the "Video Cameras Without Video: Opportunities For Sensing With Embedded Vision" tutorial at the May 2017 Embedded Vision Summit. Within the next few years, network cameras will cease to be regarded primarily as image capture devices. They will instead transform into intelligent data capture nodes whose functionality will in many, but not
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
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.
Berkeley Design Technology, Inc.
PO Box #4446
Walnut Creek, CA 94596
