1,810,952 research outputs found

    The art of CNN template design

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    A practical survey of the design rules of uncoupled and coupled linear CNN templates with binary inputs and outputs is given. The usage and the properties of the different classes of CNN templates are analyzed. CNN chip specific robustness considerations are also given

    Non-linear coupled CNN models for multiscale image analysis

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    A CNN model of partial differential equations (PDEs) for image multiscale analysis is proposed. The model is based on a polynomial representation of the diffusivity function and defines a paradigm of polynomial CNNs,for approximating a large class of nonlinear isotropic and/or anisotropic PDEs. The global dynamics of spacediscrete polynomial CNN models is analyzed and compared with the dynamic behavior of the corresponding space-continuous PDE models. It is shown that in the isotropic case the two models are not topologically equivalent: in particular discrete CNN models allow one to obtain the output image without stopping the image evolution after a given time (scale). This property represents an advantage with respect to continuous PDE models and could simplify some image preprocessing algorithm

    CNN International

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    Dr David Swann interviewed by CNN International for a special programme series profiling international designers- 90 seconds vignette showcased innovative solutions from around the world. A theme week on CNN International and CNN.com concluded with a half hour program special in September. The campaign was played to CNN’s television and online audiences with a global reach of 2 billion in 200 countries and 271 million households around the world

    BUSINESS TRAVELLER . How pod planes could change travel forever

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    Futuristic and disruptive There are several independent initiatives exploring the feasibility of modular planes, which could transform the way people and cargo travel. One of these revolutionary aircraft designs, called Clip-Air, has been created by Switzerland's Federal Polytechnic Institute. Another is the Link & Fly concept, designed by AKKA Technologies, a European engineering services firm. While the concept might be boundary-pushing, the inspiration for Clip-Air is more mundane: the humble shipping container. Despite, or perhaps because of, its simple design, the shipping container is one of the most disruptive inventions of the past century. It allows cargo to be moved cheaply from one mode of transport to another and has facilitated the development of the complex supply chains all modern economies rely on. Transfer from truck to giant cargo ship to freight train is seamless and the container can be used again and again, drastically reducing the cost of long-distance shipping. That's the magic of inter-modal transport -- and it's something this futuristic and potentially game-changing concept hopes to emulate.LI

    Zuckerberg exclusive broadcast interview on CNN\u27s ʺNew Dayʺ about internet.org launch

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    CNN\u27s New Day interviews Mark Zuckerberg about the internet.org launch in 2013https://epublications.marquette.edu/zuckerberg_files_videos/1069/thumbnail.jp

    Subtractor-Based CNN Inference Accelerator

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    This paper presents a novel method to boost the performance of CNN inference accelerators utilizing subtractors. The proposed CNN preprocessing accelerator relies on sorting, grouping, and rounding the weights in order to create combinations that allow for the replacement of one multiplication operation and addition operation by a single subtraction operation. Given the high cost of multiplication in terms of power and area, replacing it with subtraction allows for a performance boost by reducing the power and area. The proposed method allows for controlling the trade-off between the performance gains and the accuracy loss through increasing or decreasing the usage of subtractors. Using a rounding size of 0.05 on LeNet-5 with the MNIST dataset, the proposed design can achieve 32.03% power savings and a 24.59% reduction in the area at the cost of only 0.1% in terms of accuracy loss

    CNN-BiLSTM prediction (1,000).

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    CNN-BiLSTM prediction (1,000).</p

    CNN-RNN prediction (1,000).

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    CNN-RNN prediction (1,000).</p
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