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BDTI, Jabil, NVIDIA and Tryolabs Demonstration of AI-based Face Mask Detection and Analytics

BDTI and its partners, Tryolabs S.A. and Jabil Optics, are delighted to announce MaskCam: an open-source smart camera prototype reference design based on the NVIDIA Jetson Nano capable of estimating the number and percentage of people wearing face masks in its field of view. MaskCam was developed as part of an independent, hands-on evaluation of …

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“Key Trends and Challenges in Practical Visual AI and Computer Vision,” a Presentation from the Edge AI and Vision Alliance

Jeff Bier, Founder of the Edge AI and Vision Alliance and President of BDTI, presents the “Key Trends and Challenges in Practical Visual AI and Computer Vision” tutorial at the September 2020 Embedded Vision Summit. With visual AI and computer vision technologies advancing faster than ever, it can be difficult… “Key Trends and Challenges in …

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BDTI Demonstration of Computer Vision Algorithm Evaluation and Selection

Jeremy Giddings, director of business development at BDTI, demonstrates the company’s latest embedded vision technologies and products at the 2019 Embedded Vision Summit. Specifically, Giddings shows the detailed approach BDTI takes in evaluating and selection computer vision algorithms for its clients. One of BDTI’s clients, a major consumer products manufacturer, needed a background subtraction algorithm …

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Strawberries

Deep Learning Economies of Scale: How Real-World Computer Vision is Changing

This article was originally published by BDTI. It is reprinted here with the permission of BDTI. When we launched the Embedded Vision Alliance in 2011, we did so out of the conviction that computer vision was ready to become a ubiquitous technology that would be used to solve numerous important, real-world problems. And, indeed, it’s …

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BDTI Demonstration of a Neural Network on a Low-Power Embedded Processor

Jeremy Giddings, director of business development at BDTI, delivers a product demonstration at the May 2018 Embedded Vision Summit. This demo shows an extremely lightweight implementation of a neural network trained for people detection. Starting with the open-source YOLO (You Only Look Once) network, BDTI pruned layers and performed 8-bit quantization, creating an optimized implementation …

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BDTI Demonstration of Algorithm Restructuring and Optimization for Real-Time Performance

Jeremy Giddings, director of business development at BDTI, delivers a product demonstration at the May 2018 Embedded Vision Summit. This demo shows the real-time performance of Google’s 3D sensing algorithms on the Lenovo Phab 2 Pro smartphone. The Phab 2 Pro, the first commercial product with Google’s 3D sensing technology, is the result of BDTI’s …

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BDTI Demonstration of Object Detection and Measurement Using a Stereo Camera

Jeremy Giddings, director of business development at BDTI, delivers a product demonstration at the May 2018 Embedded Vision Summit. This demo showcases BDTI’s expertise in design and development of vision-based applications. BDTI engineers implemented a version of the MobileNet-SSD neural network for detecting people within the video stream, then used the Intel RealSense SDK to …

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“The Four Key Trends Driving the Proliferation of Visual Perception,” a Presentation from the Embedded Vision Alliance

Jeff Bier, Founder of the Embedded Vision Alliance and Co-founder and President of BDTI, presents the “Four Key Trends Driving the Proliferation of Visual Perception” tutorial at the May 2018 Embedded Vision Summit. With so much happening in computer vision applications and technology, and happening so fast, it can be difficult to see the big …

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Data Sets for Machine Learning Model Training

Deep learning and other machine learning techniques have rapidly become a transformative force in computer vision. Compared to conventional computer vision techniques, machine learning algorithms deliver superior results on functions such as recognizing objects, localizing objects within a frame, and determining which pixels belong to which object. Even problems like optical flow and stereo correspondence, …

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Implementing Vision with Deep Learning in Resource-constrained Designs

DNNs (deep neural networks) have transformed the field of computer vision, delivering superior results on functions such as recognizing objects, localizing objects within a frame, and determining which pixels belong to which object. Even problems like optical flow and stereo correspondence, which had been solved quite well with conventional techniques, are now finding even better …

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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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