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

BDTI, Blog Posts /

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

BDTI, Summit 2018, Videos /

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

BDTI, Summit 2018, Videos /

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

BDTI, Summit 2018, Videos /

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

Algorithms, BDTI, Edge AI and Vision Alliance, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

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

AImotive, Algorithms, Articles, BDTI, Edge AI and Vision Alliance, iMerit, LUXOFT, Object Identification, Processors, Software, Technical Articles, Tools /

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

Algorithms, Articles, Au-Zone Technologies, BDTI, Edge AI and Vision Alliance, Processors, Software, Synopsys, Technical Articles, Tools /

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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Software Frameworks and Toolsets for Deep Learning-based Vision Processing

Algorithms, AMD, Articles, Au-Zone Technologies, BDTI, Edge AI and Vision Alliance, MVTec, Processors, Software, Synopsys, Technical Articles, Tools /

This article provides both background and implementation-detailed information on software frameworks and toolsets for deep learning-based vision processing, an increasingly popular and robust alternative to classical computer vision algorithms. It covers the leading available software framework options, the root reasons for their abundance, and guidelines for selecting an optimal approach among the candidates for a

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“Demystifying Deep Neural Networks,” a Presentation from BDTI

Algorithms, BDTI, Processors, Software, Tools, Videos /

Shehrzad Qureshi, Senior Engineer at BDTI, presents the "Demystifying Deep Neural Networks" tutorial at the May 2017 Embedded Vision Summit. What are deep neural networks, and how do they work? In this talk, Qureshi provides an introduction to deep convolutional neural networks (CNNs), which have recently demonstrated impressive success on a wide range of vision

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Figure3

Deep Learning for Object Recognition: DSP and Specialized Processor Optimizations

Algorithms, Articles, BDTI, Cadence, Edge AI and Vision Alliance, Intel, Processors, Software, Synopsys, Technical Articles, Tools /

Neural networks enable the identification of objects in still and video images with impressive speed and accuracy after an initial training phase. This so-called "deep learning" has been enabled by the combination of the evolution of traditional neural network techniques, with one latest-incarnation example known as a CNN (convolutional neural network), by the steadily increasing

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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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