The Winograd Transformation


Cheng Wang, senior vice president of engineering at Flex Logix, explains how the Winograd Transformation applies to convolutional neural networks. https://youtu.be/E7QJUby9x-I » read more

Computer Vision Sees a Bright Future


Computer vision is powering advances in automotive, medical, consumer, and agriculture markets. Because the world of computer vision coupled with machine learning evolves so quickly, teams need a way to design and verify an algorithm while the specifications and requirements evolve without starting over every time there is a change. The only way to successfully develop these systems is to use h... » read more

Week in Review: IoT, Security, Auto


Internet of Things The drone episode last month at Gatwick Airport in the United Kingdom forced the cancellation or diversion of more than 1,000 flights over three days. While local police arrested a couple suspected of being behind the drone flights, they were quickly exonerated and released. Questions remain on how airports should respond to such episodes, which are bound to happen again and... » read more

System Bits: Dec. 26


Adding learning to computer vision UCLA’s Samueli School of Engineering and Stanford University are working on advanced computer vision technology, using artificial intelligence to help vision systems learn to identify faces, objects and other things on their own, without training by humans. The research team breaks up images into chunks they call “viewlets,” then they have the computer ... » read more

Processors Are Exciting Again


Today is a very exciting time in the world of processor architectures. Domain-specific processor architectures are now fully realized as the best answers to the challenges of low power and high performance for many applications. Advancements in artificial intelligence are leading the way to exciting new experiences and products today and in our future. There have been more advances in deep lear... » read more

Low-Latency Image Acquisition And Processing With A Programmable Vision-System-On-Chip


This work aims to demonstrate the benefits of using a Vision-System-on-Chip for image processing tasks with very high latency demands between image acquisition and processing. By leveraging a column-parallel, mixed-signal data path, which is entirely software-defined by three application-specific instruction- set processors (ASIPs), image data within multiple regions of interest can be analyzed... » read more

System Bits: Aug. 7


ML leverages existing hospital patient data to detect trouble Focusing on emergency and critical care patients, a University of Michigan spinout, Fifth Eye, has developed a system that combines a machine learning algorithm with signal processing to monitor the autonomic nervous system of hospital patients and interprets the data every two minutes, which can sometimes be almost two days faster ... » read more

Synthesizing Computer Vision Designs To Hardware


Computer vision is one of the hottest markets in electronic design today. Digital processing of images and video with complex algorithms in order to interpret meaning has almost as many applications and markets as there are uses for the human eye. The biggest problem that designers face is that the computer vision system requirements and algorithms change quickly and often. Even the targ... » read more

Accelerate Computer Vision Design Using High-Level Synthesis


Computer vision solutions are all around us, in cars, consumer products, security, retail, and agriculture. But, designing these solutions is not easy, mainly because of constant algorithm upgrades and related requirements changes. This means that wherever the team is in the RTL creation and verification flow, they might have to start over, which can cause an unacceptable delay in the productio... » read more

Week in Review: IoT, Security, Auto


Cybersecurity Rambus signed a patent license agreement with Socionext, a designer of system-on-a-chip devices. Socionext will use Rambus technology in memory controllers, serializers/deserializers, and security applications. Netskope acquired Sift Security, adding 10 technical employees to its headcount of more than 500 people; financial terms weren’t revealed. Sift CEO Neil King was tapp... » read more

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