FPGAs have proven to be a compelling solution for solving deep learning problems, particularly when applied to image recognition. The advantage of using FPGAs for deep learning is primarily derived from several factors: their massively parallel architectures, efficient DSP resources, and large amounts of on-chip memory and bandwidth. An illustration of a typical FPGA architecture […]
FPGAs for Deep Learning-based Vision Processing Read More +
Neural networks enable the identification of objects in still and video images with impressive speed and accuracy after an initial training phase. This so-called "deep learning" has been enabled by the combination of the evolution of traditional neural network techniques, with one latest-incarnation example known as a CNN (convolutional neural network), by the steadily increasing
Deep Learning for Object Recognition: DSP and Specialized Processor Optimizations Read More +
Bill Jenkins, Senior Product Specialist for High Level Design Tools at Intel, presents the "Accelerating Deep Learning Using Altera FPGAs" tutorial at the May 2016 Embedded Vision Summit. While large strides have recently been made in the development of high-performance systems for neural networks based on multi-core technology, significant challenges in power, cost and, performance
“Accelerating Deep Learning Using Altera FPGAs,” a Presentation from Intel Read More +
Yury Gorbachev, Principal Engineer at Itseez (now part of Intel), presents the "Real-world Vision Systems Design: Challenges and Techniques" tutorial at the May 2016 Embedded Vision Summit. Computer vision is central to many modern, cool products and technologies, including augmented reality, virtual reality and drones. Thanks to recent advances in system-on-chip and embedded systems design,
“Real-world Vision Systems Design: Challenges and Techniques,” a Presentation from Intel Read More +
FLIR's New Boson™ Thermal Camera Core to Feature Onboard Visual Intelligence Computing Through Custom Implementation of Myriad 2 VPU SAN MATEO, CA–(Marketwired – Apr 18, 2016) – Movidius, the leader in low-power machine vision, today announced a strategic collaboration with FLIR Systems, a global leader in thermal imaging technology, to bring advanced computer vision capabilities
This technical article was originally published at Altera's website. It is reprinted here with the permission of Altera. Deep learning neural network systems currently provide the best solution to many large computing problems for image recognition and natural language processing. Neural networks are inspired by biological systems, in particular the human brain; they use conventional
The substantial resources available in modern programmable logic devices, in some cases including embedded processor cores, makes them strong candidates for implementing vision-processing functions. The rapidly maturing OpenCL framework enables the rapid and efficient development of programs that execute across programmable logic fabric and other heterogeneous processing elements within a system. As mentioned in the
OpenCL Streamlines FPGA Acceleration of Computer Vision Read More +
Yury Gorbachev, Principal Engineer at Itseez (now part of Intel), presents the "OpenCV for Embedded: Lessons Learned" tutorial at the May 2015 Embedded Vision Summit. OpenCV is the most widely used software component library for computer vision. Initially used mainly for algorithm development and prototyping, in recent years OpenCV has also been used extensively for
“OpenCV for Embedded: Lessons Learned,” a Presentation from Intel Read More +
Deshanand Singh, Director of Software Engineering at Altera, presents the "Efficient Implementation of Convolutional Neural Networks using OpenCL on FPGAs" tutorial at the May 2015 Embedded Vision Summit. Convolutional neural networks (CNN) are becoming increasingly popular in embedded applications such as vision processing and automotive driver assistance systems. The structure of CNN systems is characterized
This article was originally published on June 10, 2015 at Altera's website. It is reprinted here with the permission of Altera. Papers at this year’s Embedded Vision Summit suggested the vast range of ways that embedded systems can employ focused light as an input, and the even vaster range of algorithms and hardware implementations they
Sorting Out Embedded Vision Systems Read More +
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