Imagination Technologies

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Cloud and Edge Vision Processing Options for Deep Learning Inference

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Should deep learning-based computer vision processing take place in the cloud, at the edge, or both? This seemingly simple question has a complicated answer: "it depends." This article provides perspectives on the various factors you should consider, and with what priorities, when making this implementation decision for your particular project's requirements. THe Edge-Centric Inference Evolution […]

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“Object Detection for Embedded Markets,” a Presentation from Imagination Technologies

Algorithms, Imagination Technologies, Object Identification, Object Tracking, Processors, Software, Summit 2019, Tools, Videos /

Paul Brasnett, PowerVR Business Development Director for Vision and AI at Imagination Technologies, presents the “Object Detection for Embedded Markets” tutorial at the May 2019 Embedded Vision Summit. While image classification was the breakthrough use case for deep learning-based computer vision, today it has a limited number of real-world applications. In contrast, object detection is

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“Mining Site Data Extraction Using 3D Machine Learning,” a Presentation from Strayos

Algorithms, Imagination Technologies, Processors, Sensors and Cameras, Software, Strayos, Summit 2019, Tools, Videos /

Ravi Sahu, Founder and CEO of Strayos, presents the "Mining Site Data Extraction Using 3D Machine Learning" tutorial at the May 2019 Embedded Vision Summit. This talk focuses on extracting invariant features for segmentation of 3D models of mining sites. The image data is generated by stitching together geo-tagged images from a drone. The 3D

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PowerVR GPU and NNA Available On SiFive Platform

Imagination Technologies, News /

Imagination Technologies joins SiFive’s DesignShare Ecosystem, Enabling RISC-V users to access industry-leading IP London, UK; and San Mateo, California; 13th May 2019 – Imagination Technologies announces that it has joined SiFive’s DesignShare ecosystem, giving system designers easy access to its industry-leading PowerVR GPU and neural network accelerator (NNA) IP cores. The PowerVR GPU will be

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Combining an ISP and Vision Processor to Implement Computer Vision

Algorithms, Articles, Imagination Technologies, Processors, Sensors and Cameras, Software, Synopsys, Technical Articles, Tools /

An ISP (image signal processor) in combination with one or several vision processors can collaboratively deliver more robust computer vision processing capabilities than vision processing is capable of providing standalone. However, an ISP operating in a computer vision-optimized configuration may differ from one functioning under the historical assumption that its outputs would be intended for

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“Improving and Implementing Traditional Computer Vision Algorithms Using DNN Techniques,” a Presentation from Imagination Technologies

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Paul Brasnett, Senior Research Manager for Vision and AI in the PowerVR Division at Imagination Technologies, presents the “Improving and Implementing Traditional Computer Vision Algorithms Using DNN Techniques” tutorial at the May 2018 Embedded Vision Summit. There has been a very significant shift in the computer vision industry over the past few years, from traditional

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“Training CNNs for Efficient Inference,” a Presentation from Imagination Technologies

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Paul Brasnett, Principal Research Engineer at Imagination Technologies, presents the "Training CNNs for Efficient Inference" tutorial at the May 2017 Embedded Vision Summit. Key challenges to the successful deployment of CNNs in embedded markets are in addressing the compute, bandwidth and power requirements. Typically, for mobile devices, the problem lies in the inference, since the

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“Training CNNs for Efficient Inference,” a Presentation from Imagination Technologies

Algorithms, Imagination Technologies, Processors, Software, Tools, Videos /

Paul Brasnett, Principal Research Engineer at Imagination Technologies, presents the "Training CNNs for Efficient Inference" tutorial at the May 2017 Embedded Vision Summit. Key challenges to the successful deployment of CNNs in embedded markets are in addressing the compute, bandwidth and power requirements. Typically, for mobile devices, the problem lies in the inference, since the

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Imagination’s Smart, Efficient Approach to Mobile Compute

Articles, Imagination Technologies, Technical Articles /

This article was originally published at Imagination Technologies' website, where it is one of a series of articles. It is reprinted here with the permission of Imagination Technologies. Imagination designed its PowerVR Tile-Based Deferred Rendering (TBDR) graphics architecture more than 20 years ago with a focus on efficiency across performance, power consumption and system level

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Measuring GPU Compute Performance

Articles, Imagination Technologies, Technical Articles /

This article was originally published at Imagination Technologies' website, where it is one of a series of articles. It is reprinted here with the permission of Imagination Technologies. After exploring a quick guide to writing OpenCL kernels for PowerVR Rogue GPUs and analyzing a heterogeneous compute case study focused on image convolution filtering, I am

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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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