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CNNs for NLP in the Browser: Client-Side Deployment and Visualization Opportunities

机译:浏览器中用于NLP的CNN:客户端部署和可视化机会

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摘要

We demonstrate a JavaScript implementation of a convolutional neural network that performs feedforward inference completely in the browser. Such a deployment means that models can run completely on the client, on a wide range of devices, without making backend server requests. This design is useful for applications with stringent latency requirements or low connectivity. Our evaluations show the feasibility of JavaScript as a deployment target. Furthermore, an in-browser implementation enables seamless integration with the JavaScript ecosystem for information visualization, providing opportunities to visually inspect neural networks and better understand their inner workings.
机译:我们演示了卷积神经网络的JavaScript实现,该实现完全在浏览器中执行前馈推理。这种部署意味着模型可以在客户端,各种设备上完全运行,而无需发出后端服务器请求。此设计对于具有严格延迟要求或低连接性的应用程序很有用。我们的评估显示了JavaScript作为部署目标的可行性。此外,浏览器内实现可实现与JavaScript生态系统的无缝集成,以实现信息可视化,从而提供可视化检查神经网络并更好地了解其内部工作的机会。

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