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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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Intel Works with University of Pennsylvania in Using Privacy-Preserving AI to Identify Brain Tumors

What’s New: Intel Labs and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) are co-developing technology to enable a federation of 29 international healthcare and research institutions led by Penn Medicine to train artificial intelligence (AI) models that identify brain tumors using a privacy-preserving technique called federated learning. Penn Medicine’s work

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Hope on the AI Horizon for Data Privacy

This blog post was originally published by Bitfury. It is reprinted here with the permission of Bitfury. Each of us has been giving away our valuable data, for free, for more than 15 years. We do not have any real control of this personal data, nor how it is being processed, or why, or by

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Protecting Privacy in a Data-Driven World: Privacy-Preserving Machine Learning

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. Privacy for machine learning (ML) and other data-intensive applications is increasingly threatened by sophisticated methods of re-identifying anonymized data. In addition, while encryption helps preserve privacy while data is stored on hard drives or moving over networks,

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Exploring Deep Learning Face Recognition with Thermal Images

This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. Interactions with computer systems frequently benefit from the ability to detect information about the user or use environment. Image processing and analyzing techniques, including deep neural networks (DNNs), are often used for this purpose. However, many promising

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“Designing Home Monitoring Cameras for Scale,” a Presentation from Ring

Ilya Brailovskiy, Principal Engineer, and Changsoo Jeong, Head of Algorithm, both of Ring, present the "Optimizing SSD Object Detection for Low-power Devices" tutorial at the May 2019 Embedded Vision Summit. In this talk, Brailovskiy and Jeong discuss how Ring designs smart home video cameras to make neighborhoods safer. In particular, they focus on three key

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“Balancing Safety, Convenience and Privacy in the Era of Ubiquitous Cameras,” a Presentation from Intel

Charlotte Dryden, Director of the Visual Computing Developer Solutions team at Intel, presents the “Balancing Safety, Convenience and Privacy in the Era of Ubiquitous Cameras” tutorial at the May 2018 Embedded Vision Summit. Computer vision-enabled cameras are proliferating rapidly and will soon be ubiquitous – in, on and around vehicles, homes, toys, stores, public transit,

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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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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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