Tag Archive : Vision

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Microsoft and Team Gleason, the nonprofit organization founded by NFL player Steve Gleason, today launched Project Insight to create an open dataset of facial imagery of people with amyotrophic lateral sclerosis (ALS). The organizations hope to foster innovation in computer vision and broaden the potential for connectivity and communication for people with accessibility challenges.

Microsoft and Team Gleason assert that existing machine learning datasets don’t represent the diversity of people with ALS, a condition that affects as many as 30,000 people in the U.S. This results in issues accurately identifying people, due to breathing masks, droopy eyelids, watery eyes, and dry eyes from medications that control excessive saliva.

Project Insight will investigate how to use data and AI with the front-facing camera already present in many assistive devices to predict where a person is looking on a screen. Team Gleason will work with Microsoft’s Health Next Enable team to gather

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A camera or a computer: How the architecture of new home security vision systems affects choice of memory technology

A long-forecast surge in the number of products based on artificial intelligence (AI) and machine learning (ML) technologies is beginning to reach mainstream consumer markets.

It is true that research and development teams have found that, in some applications such as autonomous driving, the innate skill and judgement of a human is difficult, or perhaps even impossible, for a machine to learn. But while in some areas the hype around AI has run ahead of the reality, with less fanfare a number of real products based on ML capabilities are beginning to gain widespread interest from consumers. For instance, intelligent vision-based security and home monitoring systems have great potential: analyst firm Strategy Analytics forecasts growth in the home security camera market of more than 50% in the years between 2019 and

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Imagine being able to embark on a real-time computer vision project in a few hours, with no code to build a traffic control system, a warehouse monitoring system, or an in-store point of sale optimization system. Like the apps that are built on top of smartphone operating systems, these smart computer vision projects can use a multitude of proprietary and vendor algorithms. Because they are built on top of BrainFrame, an operating system for computer vision that comes with a Smart Vision AI Developers Kit, they take a fraction of the time to build than other computer vision projects.

BrainFrame is one of the core products of Aotu.ai, started by two founders, Stephen Li and Alex Thiel. Stephen applied his experience building out the Android operating system to BrainFrame. In collaboration with leading chipmakers such as Intel, Nvidia, etc., BrainFrame is positioning itself to

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Exer Labs has raised $2 million in funding and it has unveiled its AI and computer vision Exer Studio app for the Mac that captures your movements for coaching advice and Peloton-style leaderboards for workouts.

The Denver-based fitness startup captures your movements with your laptop’s camera and evaluates your form. It can share your results with friends, fitness coaches, or others to see where you rank on the leaderboards, motivating you to work harder or faster.

CEO Zaw Thet said in an interview with VentureBeat that Exer relies on edge-based AI (meaning it uses your smartphone’s computing power) and computer vision to power its motion coaching platform. It offers real-time audio and visual feedback via a Mac (and its camera), on almost any type of human motion, without having a human in the loop. The mission is to help people move, train, and play better. Coaches can use the app

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Computer vision

October 8, 2020 | computer | No Comments

Teaching computers to see more sharply with processing in the cloud


At the Lawrence J. Ellison Institute for Transformative Medicine of USC, scientists have trained a neural network to spot different types of breast cancer on a small data set of less than 1,000 images. Instead of educating the AI system to distinguish between groups of samples, the researchers taught the network to recognize the visual “tissue fingerprint” of tumors so that it could work on much larger, unannotated data sets.

Halfway across the country in suburban Chicago, Oracle’s construction and engineering group is working with video-camera and software companies to build an artificial intelligence system that can tell from live video feeds—with up to 92% accuracy—whether construction workers are wearing hard hats and protective vests and practicing social distancing.

Such is the promise of computer vision, whereby machines are trained to interpret and understand the physical world around them, oftentimes spotting and comparing fine visual cues the human eye

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Opinions expressed by Entrepreneur contributors are their own.


Covid-19 has brought about a paradigm shift across industries, and venture investing is no exception. The pandemic and ensuing lockdowns have influenced consumer behaviour and preferences majorly, may be even permanently in some cases.

To understand how the investment landscape has transitioned amidst the Covid-19 pandemic and its impact on long-term investing, Entrepreneur India interacted with Vinnie Lauria, founding partner, Golden Gate Ventures, an early-stage venture capital (VC) firm in Southeast Asia. Lauria shared his views on the nitty-gritty of investments along with the bounce back plan for businesses.

Impact of Pandemic on Investment and Bounce Back Approach

Most of the work operations continue to be remote in Singapore and Indonesia despite lifting of lockdown restrictions. “In a market like Indonesia, people are working from home and locked down. There were certain presumptions about bounce back

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Computer vision brings shoppable video to life

September 28, 2020 | computer | No Comments

30-second summary:

  • Computer vision is a long-established segment of AI which deals with a machine’s ability to understand and process visuals and provide appropriate outputs.
  • But as computer vision is developed and refined, it is increasingly being used in retail marketing to understand consumer needs and streamline the purchase process through channels such as shoppable video.
  • Brands and retailers can upload entire catalogs and use computer vision to map all products contained within them. These products can be automatically recognized within video content without retailers having to spend hours tagging or assigning them manually.
  • Shoppable video with computer vision enables the consumer to open and browse curated product selections without navigating away from the video or being redirected through multiple pages and links.
  • AI enables deep and ongoing evaluation of visual content to help brands and retailers refine and optimize their video strategies. It allows them to move beyond generic
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During my career as an automotive engineer at Ford Motor Company in the early 2000s, world-class vision system technology was already routinely being used for various applications on programs and production. However, the automation around the analysis had not yet come full circle. Today, it has. And with the latest iterations of smartphones for facial recognition and other functionality, most anyone with a smartphone already has a device using computer vision. Machine and computer vision are also being used in applications such as satellite geo-analytics, food safety and processing, agriculture operations, augmented reality, human emotion analysis, medical diagnostics, robotic guidance, quality control, transportation coordination, utilities, security surveillance, and more.

As the technology proliferates across new sectors, it will be critical for business leaders to assess how computer vision could impact the trajectory of their organization. So let’s take a deeper look at the real-world use cases emerging today. (For the

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MONTREAL–(BUSINESS WIRE)–Immervision, the Montreal-based leader in wide-angle intelligent vision, introduces JOYCE, the first humanoid robot developed by the computer vision community to help machines gain human-like perception and beyond.

Watch the video: https://vimeo.com/458617443

The purpose of JOYCE is to further advance computer vision technologies by inviting the community to help JOYCE gain a better understanding of her environment by upgrading her optics, sensors and AI algorithms.

To support the realization of this complex task, Immervision is also unveiling the JOYCE Development Kit for engineers and AI developers. This “JOYCE IN A BOX” development kit is equipped with three ultra-wide-angle panomorph cameras calibrated to give 2D hemispheric, 3D stereoscopic hemispheric or full 360 x 360 spherical capture and viewing of the environment. It uses data-In-picture technology so that each of her video frames can be enriched with data from a wide array of sensors providing contextual information to AI

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