Phil Lapsley, Co-founder and Vice President of BDTI, presents the “Five Things You Might Overlook on Your Next Vision-enabled Product Design” tutorial at the May 2023 Embedded Vision Summit. When you think about building a vision-enabled product, you probably think about things like: Which processor am I going to use? What neural network will it […]
David Davis, Senior Embedded Software Engineer, and John Withers, Automation and Systems Engineer, both of BDTI, present the “TensorFlow Lite for Microcontrollers (TFLM): Recent Developments” tutorial at the May 2022 Embedded Vision Summit. TensorFlow Lite Micro (TFLM) is a generic inference framework designed to run TensorFlow models on digital signal processors (DSPs), microcontrollers and other
Evan Juras, Computer Vision Engineer at BDTI, presents the “Tools and Strategies for Quickly Building Effective Image Datasets,” tutorial at the May 2021 Embedded Vision Summit. A common pain point when using machine learning for computer vision is the need to manually curate and label large quantities of training images. Depending on the application, thousands
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 that counts the number of
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
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 to see the big picture.
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
BDTI Demonstration of Computer Vision Algorithm Evaluation and Selection Read More +
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
Deep Learning Economies of Scale: How Real-World Computer Vision is Changing Read More +
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
BDTI Demonstration of a Neural Network on a Low-Power Embedded Processor Read More +
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
BDTI Demonstration of Algorithm Restructuring and Optimization for Real-Time Performance Read More +
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