Wide angle cameras are hot in smartphones, cars, VR and surveillance, for convenience, cost or safety. Turning wide-angle, high-res input into pleasing and usable high-resolution output in real-time depends on a holistic solution with special optics, dedicated hardware and customized software. Recent-release phones have three cameras, for the iPhone 11 a wide-angle lens, a telephoto […]
Ultra-Wide is Ultra-Hot, and a Lot of Work Read More +
This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. XGBoost is a widely used machine learning library, which uses gradient boosting techniques to incrementally build a better model during the training phase by combining multiple weak models. Weak models are generated by computing the gradient descent using
Learning to Rank with XGBoost and GPU Read More +
This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. Back in 2018, Intel launched the Intel® Distribution of OpenVINO™ toolkit. Since then, it’s been widely adopted by partners and developers to deploy AI-powered applications in various industries, from self-checkout kiosks to medical imaging to industrial robotics.
Joseph Spisak, Product Manager at Facebook, delivers the presentation “PyTorch Deep Learning Framework: Status and Directions” at the Embedded Vision Alliance’s December 2019 Vision Industry and Technology Forum. Spisak gives an update on the Torch deep learning framework and where it’s heading.
“PyTorch Deep Learning Framework: Status and Directions,” a Presentation from Facebook Read More +
Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, delivers the presentation “Current and Planned Standards for Computer Vision and Machine Learning” at the Embedded Vision Alliance’s December 2019 Vision Industry and Technology Forum. Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the
Pavan Kumar, Co-founder and CTO of Cocoon Health (formerly Cocoon Cam), delivers the presentation “Edge/Cloud Tradeoffs and Scaling a Consumer Computer Vision Product” at the Embedded Vision Alliance’s September 2019 Vision Industry and Technology Forum. Kumar explains how his company is evolving its use of edge and cloud vision computing in continuing to bring new
Raghuraman Krishnamoorthi, Software Engineer at Facebook, delivers the presentation “Quantizing Deep Networks for Efficient Inference at the Edge” at the Embedded Vision Alliance’s September 2019 Vision Industry and Technology Forum. Krishnamoorthi gives an overview of practical deep neural network quantization techniques and tools.
Tom Hackenberg, Principal Analyst at IHS Markit, presents the “Embedded Vision Applications Lead Way for Processors in AI: A Market Analysis of Vision Processors” tutorial at the May 2019 Embedded Vision Summit. Artificial intelligence is not a new concept. Machine learning has been used for decades in large server and high performance computing environments. Why
Chris Osterwood, Founder and CEO of Capable Robot Components, presents the “How to Choose a 3D Vision Sensor” tutorial at the May 2019 Embedded Vision Summit. Designers of autonomous vehicles, robots and many other systems are faced with a critical challenge: Which 3D vision sensor technology to use? There are a wide variety of sensors
“How to Choose a 3D Vision Sensor,” a Presentation from Capable Robot Components Read More +
Bert Moons, Hardware Design Architect at Synopsys, presents the “Five+ Techniques for Efficient Implementation of Neural Networks” tutorial at the May 2019 Embedded Vision Summit. Embedding real-time, large-scale deep learning vision applications at the edge is challenging due to their huge computational, memory and bandwidth requirements. System architects can mitigate these demands by modifying deep
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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