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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.

Edge AI and Privacy

As sensors and AI proliferate in our devices and our environment, people are understandably concerned about the potential erosion of privacy. For example, there has recently been much discussion in the media about face recognition technology, and some governments have begun to regulate its use.

It may initially seem that the proliferation of sensors and AI must lead to loss of privacy. In reality, it’s possible to design intelligent, perceptive devices in ways that deliver valuable capabilities while protecting privacy. An early example of this is the Netatmo Welcome, a smart home monitoring camera that can be configured to disable video recording when familiar faces are present.

The purpose of this privacy portal is to facilitate awareness of the challenges and opportunities at the intersection of privacy, edge AI and machine perception.

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Cameras-Everywhere

Computer Vision Solutions and Privacy-by-Design

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. These days cameras are ubiquitous – in our smart phones, our cars, homes, and around our cities. And opportunities for computer vision are endless, extending across robotics, retail, healthcare, transportation, and even sustainable agriculture. Computer vision offers

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Tend Secure Lynx A

Privacy in the Era of Ubiquitous Cameras and AI

This blog post was originally published in the late July 2017 edition of BDTI’s InsideDSP newsletter. It is reprinted here with the permission of BDTI. Lately I’ve been thinking about the relationship between embedded vision and privacy. Surveillance cameras are nothing new, of course. For decades, they’ve been ubiquitous in and around restaurants, stores, banks,

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“Should Visual Intelligence Reside in the Cloud or at the Edge? Trade-offs in Privacy, Security and Performance,” a Presentation from Silk Labs

Andreas Gal, CEO of Silk Labs, presents the "Should Visual Intelligence Reside in the Cloud or at the Edge? Trade-offs in Privacy, Security and Performance" tutorial at the May 2016 Embedded Vision Summit. The Internet of Things continues to expand and develop, including more intelligent connected devices that respond to people’s needs and alert them

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EE_Times-logo

Automated Face Analysis Gets Real

By Brian Dipert Editor-in-Chief, Embedded Vision Alliance This blog post was originally published at EE Times' SoC Design Line. It is reprinted here with the permission of EE Times. This week, I've invited my colleague Brian Dipert to share his perspective on various face analysis algorithms used in embedded vision. As Editor-in-Chief of the Embedded

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SceneTapiPhone

SceneTap: A Face Detection Privacy Flap

Back in September of last year, I introduced you to SceneTap, a service that uses webcams to provide a dynamically updated count of how many people are currently in a bar, restaurant, etc…along with estimates of male-to-female and age ratios, thereby implementing not only human face detection but also rudimentary face recognition (gender and age,

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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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