Now available—the Embedded Vision Summit On-Demand Edition! Gain valuable computer vision and edge AI insights and know-how from the experts at the 2021 Summit.


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Practical AI and computer vision technology is being developed for systems that span virtually every application, and many of these application areas will experience huge growth rates. With trendsetting products demonstrating what is possible, system designers have discovered that the suppliers of computer vision technology have removed the barriers to building practical computer vision systems—unleashing a huge wave of innovation for new products and applications.

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FRAMOS Sensor Module Ecosystem Supporting GMSL2 for Flexible Cable Routing and Ease of Installation into Small Spaces

7/28/21 – FRAMOS offers camera data transfer over a single coax cable using the GMSL2 protocol on the Jetson AGX Xavier platform. Camera developers utilizing the FRAMOS Sensor Module Ecosystem can integrate the highly flexible GMSL2 technology with image sensors producing up to 8MP resolution at 30fps over cable length of 15m. Developers benefit from

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“A Mask Detection Smart Camera Using the Nvidia Jetson Nano: System Architecture and Developer Experience,” a Presentation from BDTI and Tryolabs

Evan Juras, Computer Vision Engineer at BDTI, and Braulio Ríos, Machine Learning Engineer at Tryolabs, co-present the “A Mask Detection Smart Camera Using the Nvidia Jetson Nano: System Architecture and Developer Experience” tutorial at the May 2021 Embedded Vision Summit. MaskCam is a prototype reference design for a smart camera… “A Mask Detection Smart Camera

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AI Advancements Driving Autonomous Vehicle Ubiquity

Advances in Edge Computing Must Innovate for Autonomous Vehicles to Realize Their Potential Large numbers of sensors, massive amounts of data, ever-increasing computing power, real-time operation and security concerns required for autonomous vehicles are driving the core of computation from the cloud to the edge of the network. Autonomous vehicles are constantly sensing and sending

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Case Study: Genetic Screening Using CNNs in PerceptiLabs

This article was originally published at PerceptiLabs’ website. It is reprinted here with the permission of PerceptiLabs. One group of scientists leveraging ML is the Buchser lab at Washington University in Saint Louis School of Medicine in the Department of Genetics. There, Dr. Buchser and his team are working in functional genomics, High-Throughput Screening, and

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End-to-end HiL Testing with aiSim to Maximize Coverage

This blog post was originally published at AImotive’s website. It is reprinted here with the permission of AImotive. The aiSim team adapted the Hardware-In-the-Loop testing approach with a unique spin on the concept that allows for testing complete automated driving systems with live simulated sensor data without any prerecorded footage. In this post, we will

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Building Real-time Dermatology Classification with NVIDIA Clara AGX

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The most commonly diagnosed cancer in the US today is skin cancer. There are three main variants: melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Though melanoma only accounts for roughly 1% of all skin

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Electric Vehicle Pioneer Arrival Partners With Ambarella to Deliver Advanced Driver Assistance Systems (ADAS)

Arrival Selects Ambarella AI Vision Processor to Enable Autonomous Driving and ADAS Features SANTA CLARA, Calif. June 30, 2021—Ambarella, Inc. (NASDAQ: AMBA), an AI vision silicon company, today announced that Arrival (NASDAQ: ARVL), the global company creating electric vehicles (EVs) with its unique technologies, has selected the Ambarella CV2FS CVflow® AI vision processor for the environmental perception

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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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